內容來自 DataSciComp，人工智能/數據科學比賽整理平臺。
Github：iphysresearch/DataSciComp
本項目由 ApacheCN 強力支持。
全球數據智能大賽(2019)——“數字人體”賽場一：肺部CT多病種智能診斷
https://tianchi.aliyun.com/competition/entrance/231724/
6月24 - 9月09, 2019 // Host by 天池 // Prize: $900,000
Note: 賽場一“數字人體”挑戰賽以肺部CT多病種智能診斷爲課題，開放高質量CT標註數據，要求選手提出並綜合運用目標檢測、深度學習等人工智能算法，識別肺結節、索條（條索狀影）、動脈硬化或鈣化、淋巴結鈣化等多個病種，避免同一部位單病種的反覆篩查，提高檢測的速度和精度，輔助醫生進行診斷。
Entry Deadline:
Online Challenge: Build A Recommendation Engine (Powered by IBM Cloud)
https://datahack.analyticsvidhya.com/contest/build-a-recommendation-engine-powered-by-ibm-cloud/
24 Jan - 25 July, 2019 // Host by Analytics Vidhya // Prize: INR 50,000
Note: You are expected to build a high performing recommendation engine using any framework of your choice. You are encouraged to use IBM Watson Studio Apache spark based Jupyter notebook.
Entry Deadline:
WIDER Face & Person Challenge 2019
http://wider-challenge.org/2019.html
May 8 - July 25, 2019 // Host by CodaLab & ICCV 2019 & 商湯 & Amazon // Prize: cash prize and AWS credits
Note: Following the success of the First WIDER Challenge Workshop, we organize a new round of challenge in conjunction with ICCV 2019. The challenge centers around the problem of precise localization of human faces and bodies, and accurate association of identities. It comprises of four tracks:
WIDER Face Detection
http://wider-challenge.org/comingsoon.html, aims at soliciting new approaches to advance the state-of- the-art in face detection.
WIDER Pedestrian Detection
https://competitions.codalab.org/competitions/22852, has the goal of gathering effective and efficient approaches to address the problem of pedestrian detection in unconstrained environments.
WIDER Cast Search by Portrait
https://competitions.codalab.org/competitions/22833, presents an exciting challenge of searching cast across hundreds of movies.
WIDER Person Search by Language
https://competitions.codalab.org/competitions/22864, aims to seek new approaches to search person by natural language.
Entry Deadline:
"華爲雲杯"2019深圳開放數據應用創新大賽
https://opendata.sz.gov.cn/sodic2019/
2019-06-19 至 2019-09-07 // Host by 深圳市政府數據開放平臺 & 華爲 HUAWEI// Prize: 1400000元 + 300000元華爲雲資源
Note: 賽題數據：
交通數據 室內停車 公租房輪候 衛星遙感 文體公益活動 遊客預約 道路積水 深圳圖書館進館人次統計 龍崗區阪田街道交通流量 企業信用目錄 坪山區民生訴求數據 坪山區河流域和易積水道路視頻 光明區政府服務辦事大廳預約
Entry Deadline:
NeurIPS 2019: Disentanglement Challenge
https://www.aicrowd.com/challenges/neurips-2019-disentanglement-challenge
June 28th - September 24th, 2019 // Host by crowdAI & NeurIPS 2019 // Prize: 10,000 EUR x 2
Note: Given the growing importance of the field and the potential societal impact in the medical domain or fair decision making, it is high time to bring disentanglement to the real-world:
Stage 1: Sim-to-real transfer learning - design representation learning algorithms on simulated data and transfer them to the real world.
Stage 2: Advancing disentangled representation learning to complicated physical objects.
Entry Deadline:
CCKS 2019 面向金融領域的事件主體抽取
https://www.biendata.com/competition/ccks_2019_4/
05/01 - 07/30 2019 // Host by Biendata // Prize: ￥15,000
Note: 本次評測任務的主要目標是從真實的新聞語料中，抽取特定事件類型的主體。即給定一段文本T，和文本所屬的事件類型S，從文本T中抽取指定事件類型S的事件主體。
Entry Deadline:
全國高校大數據應用創新大賽
https://ai.futurelab.tv/contest_detail/4
6月8日 - 9月, 2019 // Host by 睡前FUTURE.AI // Prize: 20,000元 x 2
Note: 全國高校大數據應用創新大賽”（以下簡稱大賽）是由教育部高等學校計算機類專業教學指導委員會、中國工程院中國工程科技知識中心和聯合國教科文組織國際工程科技知識中心聯合主辦，復旦大學計算機學院承辦，面向全國高校在校學生的，年度性大數據學科競賽。 通用賽道：
大數據技術技能賽
https://ai.futurelab.tv/contest_detail/6: 大賽提供的數據和自選數據建立並訓練模型，使之能夠預測給定地區、日期和前置氣象條件下，未來7天的部分氣象要素的變化情況;
大數據與人工智能創意賽
https://ai.futurelab.tv/contest_detail/5: 本次大賽氣象大數據開放式命題賽道，提供過去5年若干城市的氣象數據，參賽選手可自主運用和擴充數據，設計一個基於氣象大數據的跨行業跨領域的應用解決方案。
Entry Deadline:
DeepFashion2 Challenge 2019
https://sites.google.com/view/cvcreative/deepfashion2?authuser=0
May 27 - July 30, 2019 // Host by CodaLab // Prize: NaN
Note: DeepFashion2 (github) is a comprehensive fashion dataset. It contains 491K diverse images of 13 popular clothing categories from both commercial shopping stores and consumers. It totally has 801K clothing clothing items, where each item in an image is labeled with scale, occlusion, zoom-in, viewpoint, category, style, bounding box, dense landmarks and per-pixel mask.There are also 873K Commercial-Consumer clothes pairs.
The dataset is split into a training set (391K images), a validation set (34k images), and a test set (67k images).
Track 1 Clothes Landmark Estimation
https://competitions.codalab.org/competitions/23095
Track 2 Clothes Retrieval
https://competitions.codalab.org/competitions/23098
Entry Deadline:
Snake Species Identification Challenge
https://www.aicrowd.com/challenges/snake-species-identification-challenge#timeline
January 21 - July 31, 2019 // Host by crowdAI // Prize: 2 x travel grant
Note: In this challenge you will be provided with a dataset of RGB images of snakes, and their corresponding species (class). The goal is to train a classification model.
Entry Deadline:
萊斯杯：全國第二屆“軍事智能機器閱讀"挑戰賽"
https://www.kesci.com/home/competition/5d142d8cbb14e6002c04e14a
2019-09-03 至 2019-10-28 // Host by Kesci // Prize: 50萬元人民幣
Note: 本次競賽提供的大規模中文閱讀理解數據集，共包含15萬餘篇的專業文章，7萬個軍事類複雜問題，每個問題對應五篇文章
Entry Deadline:
第三屆"長風杯"大數據分析與挖掘競賽
http://contest.cfdsj.cn/index/care
2019-05-15 至 2019-10-31 // Host by 長風大數據平臺 // Prize: ￥5萬
Note: 第三屆“長風杯”大數據分析與挖掘競賽是一場面向全國普通高等院校經濟與管理類、信息技術類等專業在校大學生的全國性賽事。
長風大數據平臺將向本次競賽的參賽者免費開放物流、電商、交通、公共、貿易等多行業的海量數據資源；其他生產型/服務型企業所提供真實數據。
Entry Deadline:
“添翼杯”人工智能創新應用大賽
2019-06-14 至 2019-09-20 // Host by 上海電信 // Prize: 40,000 元 x 2
Note:
智慧環保-垃圾分類圖像檢測問題: 請參賽選手利用訓練集圖片，建立算法模型，對測試集給定的物品圖片，判斷其屬於可回收垃圾的概率。
智慧教育-成績預測問題：請參賽選手利用脫敏後的初中學生過往考試情況與考試考點信息，建立算法模型，預測學生初中最後一次期末考試的成績。
Entry Deadline:
Northeastern SMILE Lab - Recognizing Faces in the Wild
https://www.kaggle.com/c/recognizing-faces-in-the-wild/overview/description
Now - August 8, 2019 // Host by Kaggle // Prize: NaN
Note: Can you determine if two individuals are related?
Entry Deadline:
2019百度之星開發者大賽
https://aistudio.baidu.com/aistudio/competition/detail/7
7月1日 - 9月23日, 2019 // Host by Baidu AIstudio // Prize: ￥112,000
Note: 本次競賽任務爲目標檢測，參賽者需要找出所給圖像中所有感興趣的目標，確定它們的位置和大小。參賽者需提供一個飛槳（PaddlePaddle）模型，模型輸出所給圖片中每個目標的信息，包括boundingbox（[x0,y0,x1,y1]）、類別信息和分數。
Entry Deadline:
2019 AIIA杯人工智能巡迴賽 中國移動“家·網”賽站
7月4-9月 2019 // Host by 中國移動 // Prize: 240,000 元
Note: 結合中國移動在AI領域的研發佈局，本次“家·網”賽站的主題是智慧家庭和智慧網絡，希望藉助AI技術構建數字家庭生態，打造動態高效的智能網絡。
智慧家庭賽題
http://open.home.10086.cn/hack/#/protal
智慧網絡賽題
http://aiia.cmri.cn/index/content_page: 任務一：網絡流量預測; 任務二：無線側故障根因分析;
Entry Deadline:
首屆中文NL2SQL挑戰賽
https://tianchi.aliyun.com/competition/entrance/231716/introduction
6月24 - 9月, 2019 // Host by 天池 // Prize: ￥十五萬
Note: 首屆中文NL2SQL挑戰賽，使用金融以及通用領域的表格數據作爲數據源，提供在此基礎上標註的自然語言與SQL語句的匹配對，希望選手可以利用數據訓練出可以準確轉換自然語言到SQL的模型。
Entry Deadline:
中文場景文字識別技術創新大賽
https://aistudio.baidu.com/aistudio/competition/detail/8
7月5日 - 9月27日, 2019 // Host by Baidu AIstudio // Prize: ￥54,000
Note: 文字識別的主要任務是對圖像區域中的文字行進行預測，返回文字行的內容。
Entry Deadline:
Reconnaissance Blind Chess
August, 13 - Oct 31, 2019 // Host by NeurIPS 2019 // Prize: $1,000USD
Note: Build the best AI bot to play reconnaissance blind chess, a challenge for making optimal decisions in the face of uncertainty. Reconnaissance blind chess is like chess except a player does not know where her opponent's pieces are a priori. Rather, she can covertly sense a chosen 3x3 square of the board each turn and also learn partial information from captures.
Entry Deadline:
Segmentation of THoracic Organs at Risk in CT images (SegTHOR)
https://competitions.codalab.org/competitions/21012
Jan. 5 - Aug 8, 2019 // Host by CodaLab & ISBI 2019 // Prize: NaN
Note: The goal of the SegTHOR challenge is to automatically segment 4 OAR: heart, aorta, trachea, esophagus. Participants will be provided with a training set 40 CT scans with manual segmentation. The test set will include 20 CT scans.
Entry Deadline:
安泰杯 —— 跨境電商智能算法大賽
7月16 - 9月16, 2019 // Host by 天池 // Prize: ￥100000
Note: 本次比賽給出若干日內來自成熟國家的部分用戶的行爲數據，以及來自待成熟國家的A部分用戶的行爲數據，以及待成熟國家的B部分用戶的行爲數據去除每個用戶的最後一條購買數據，讓參賽人預測B部分用戶的最後一條行爲數據。
Entry Deadline:
Generative Dog Images
https://www.kaggle.com/c/generative-dog-images
Now - August 9, 2019 // Host by Kaggle // Prize: $10,000
Note: Experiment with creating puppy pics
Entry Deadline:
Challenges and Opportunities in Automated Coding of COntentious Political Events (Cope 2019) @Euro CSS 2019
6/7 - 9/2, 2019 // Host by CodaLab & Euro CSS 2019 // Prize: NaN
Note: We use English online news archives from India and China as data sources to create the training and test corpora. India and China are the source and the target countries respectively in our setting.
Entry Deadline:
遙感圖像稀疏表徵與智能分析競賽
http://rscup.bjxintong.com.cn/
2019-06-01 至 2019-09-20 // Host by 中國科學院空間應用工程與技術中心 // Prize: ￥160000
Note: 本次大賽設置遙感圖像場景分類、 遙感圖像目標檢測、 遙感圖像語義分割、 遙感圖像變化檢測和 遙感衛星視頻目標跟蹤五個競賽單元，並在決賽中設置 基於華爲昇騰AI處理器的遙感圖像解譯加分賽。 組織方將提供面向各競賽單元的大規模遙感圖像精確標註數據集與標準規範的測試數據， 制定可量化的算法評測標準，通過初賽、決賽和複審答辯等多個階段的評比， 遴選出優秀的遙感圖像解譯算法，決勝出優勝團隊。
Entry Deadline:
CIKM 2019 EComm AI
https://tianchi.aliyun.com/competition/entrance/231719/
7月05 - 9月25, 2019 // Host by 天池 // Prize: 25000
Note:
Predicting User Behavior Diversities in A Dynamic Interactive Environment
https://tianchi.aliyun.com/competition/entrance/231719
Efficient and Novel Item Retrieval for Large-scale Online Shopping Recommendation
https://tianchi.aliyun.com/competition/entrance/231721
Entry Deadline:
ARIEL Data Challenge Series 2019
https://ariel-datachallenge.azurewebsites.net/
~ 15th of August 2019 // Host by ECML-PKDD 2019 // Prize: Eternal gratitude ... or a bottle of wine.
Note: ARIEL, a mission to make the first large-scale survey of exoplanet atmospheres, has launched a global competition series to find innovative solutions for the interpretation and analysis of exoplanet data. You can find our press release here.
The first ARIEL Data Challenge
https://ariel-datachallenge.azurewebsites.net/ML invites professional and amateur data scientists around the world to use Machine Learning (ML) to remove noise from exoplanet observations caused by starspots and by instrumentation.
A second ARIEL Data Challenge
https://ariel-datachallenge.azurewebsites.net/retrieval that focuses on the retrieval of spectra from simulations of cloudy and cloud-free super-Earth and hot-Jupiter data was also launched today.
A further data analysis challenge
https://ariel-datachallenge.azurewebsites.net/# to create pipelines for faster, more effective processing of the raw data gathered by the mission will be launched in June.
Entry Deadline:
The VoxCeleb Speaker Recognition Challenge
http://www.robots.ox.ac.uk/~vgg/data/voxceleb/competition.html
July 15, 2019 - Sep. 14, 2019 // Host by CodaLab // Prize: NaN
Note: The goal of this challenge is to probe how well current methods can recognize speakers from speech obtained 'in the wild'. The challenge will consists of the following two tasks:
Audio only speaker verification - Fixed training data: This task requires that participants train only on the VoxCeleb2 dev dataset for which we have already released speaker verification labels. The dev dataset contains 1,092,009 utterances from 5,994 speakers.
Audio only speaker verification - Open training data: For the open training condition, participants can use the VoxCeleb datasets and any other data (including that which is not publicly released) except the challenge's test data
Entry Deadline:
2nd 3D Face Alignment in the Wild Challenge - Dense Reconstruction from Video
https://competitions.codalab.org/competitions/23626
July 4 - Aug 15 2019 // Host by CodaLab // Prize: NaN
Note: The 2nd 3DFAW Challenge evaluates 3D face reconstruction methods on a new large corpora of profile-to-profile face videos annotated with corresponding high-resolution 3D ground truth meshes. The corpora includes profile-to-profile videos obtained under a range of conditions:
high-definition in-the-lab video,
unconstrained video from an iPhone device
Entry Deadline:
飯田産業 土地の販売価格の推定
https://signate.jp/competitions/162
6月10日 - 8月2019年 // Host by SIGNATE // Prize: ¥2,300,000
Note: 「日本語をネイティブに話せる方」
Entry Deadline:
Dunhuang Image Restoration Challenge@ICCV2019 workshop on e-Heritage
Jul 25 - Aug 16, 2019 // Host by EvalAI & ICCV 2019 // Prize: NaN
Note: In 1970s, the Dunhuang Academy is established to systematically preserve the heritage. From the study, half of them suffer from corrosion and aging. Because the paintings are created by different artists from 10 centuries, it is non-trivial for manual restoration. And therefore, we release the first Dunhuang Challenge with 600 paintings, which enables an open and public attention in the research community on data driven e-heritage restoration.
This year, the academy is proposing to collaborate with Microsoft Research and other researchers over the world, aiming to solve the automatic restoration of the wall painting using computer vision and machine learning technology.
Entry Deadline:
阿里巴巴大數據智能雲上編程大賽 —— 智聯招聘人崗智能匹配
https://tianchi.aliyun.com/competition/entrance/231728/introduction
7月24日 - 9月21, 2019 // Host by 天池 // Prize: ￥300000
Note: 本次大賽要求參賽者根據智聯招聘抽樣的經過脫敏的求職者標籤數據、職位信息、及部分求職者行爲信息、用人單位反饋信息，訓練排序模型，對求職者的職位候選集進行排序，儘可能使得雙端都滿意的職位（求職者滿意以及用人單位滿意）優先推薦。本次比賽裏，假定對於曝光給求職者的職位候選集裏，假如求職者感興趣會產生瀏覽職位行爲，瀏覽職位後，如果求職者滿意會產生主動投遞行爲。用人單位收到求職者主動投遞的簡歷後會給出是否滿意的反饋信號。
Entry Deadline:
AI開發者大賽
5月21日-9月21日, 2019 // Host by DC 競賽 & 科大訊飛 // Prize: 1000000 x 8
Note:
AI開發者大賽-工程機械核心部件壽命預測挑戰賽
AI開發者大賽-大數據應用分類標註挑戰賽
AI開發者大賽-廣告營銷反作弊算法挑戰賽
AI開發者大賽-阿爾茨海默綜合徵預測挑戰賽
Entry Deadline:
Accurate Automated Spinal Curvature Estimation
https://aasce19.grand-challenge.org/
July 8 - Aug 20, 2019 // Host by Grand Challenges & MICCAI 2019 // Prize: NaN
Note: The goal of MICCAI 2019 Challenge on accurate automated spinal curvature estimation and error correction from x-ray images is to investigate (semi-)automatic spinal curvature estimation algorithms and provide a standard evaluation framework with a set of x-ray images.
Entry Deadline:
AutoCV2: Image and video Classification
https://autodl.lri.fr/competitions/146
July 2 - Aug 20, 2019 // Host by AutoDL & NeurIPS 2019 // Prize: 4000 USD
Note: This is round 2 of AutoCV: Image + Video! This is a 2-phase challenge, see the challenge rules for details. This is the FEED-BACK PHASE. The second phase (final blind-test phase) will be run from a separate submission site, to be announced after the end of the feed-back phase.
Entry Deadline:
iFLYTEK AI 開發者大賽
http://challenge.xfyun.cn/2019/
5月21日 - 10月14日, 2019 // Host by 訊飛開放平臺 // Prize: 100萬 RMB
Note: "iFLYTEK AI 開發者大賽"是由科大訊飛發起的頂尖人工智能競賽平臺，匯聚產學研各界力量，面向全球開發者發起數據算法及創新應用類挑戰，推動人工智能前沿科學研究和創新成果轉化，培育人工智能產業人才，助力人工智能生態建設。 2019 年，第二屆 iFLYTEK AI 開發者大賽將繼續開放科大訊飛優質大數據資源及人工智能核心技術，面向全球開發者發起數據算法及創新應用類挑戰。
阿爾茨海默綜合症預測挑戰賽: 基於老年人在特定圖片描述任務中產生的語音，給定語音數據中提取出的聲學特徵、主被試對話的切分信息、人工文本轉寫結果以及對應的認知標籤，建立2分類模型預測認知標籤（正常或認知障礙）。
移動廣告反欺詐算法挑戰賽: 移動廣告反欺詐需要強大的數據作爲支撐，本次大賽提供了訊飛AI營銷雲海量的現網流量數據作爲訓練樣本，參賽選手需基於提供的樣本構建模型，預測流量作弊與否。
大數據應用分類標註挑戰賽: 選手基於提供的應用二級分類標籤以及若干隨機應用標註樣本，實現應用分類標註算法（每個應用一個標籤，以應用最主要屬性對應的標籤爲該應用的標籤）。
工程機械核心部件壽命預測挑戰賽: 由中科雲谷科技有限公司提供某類工程機械設備的核心耗損性部件的工作數據，包括部件工作時長、轉速、溫度、電壓、電流等多類工況數據。希望參賽者利用大數據分析、機器學習、深度學習等方法，提取合適的特徵、建立合適的壽命預測模型，預測核心耗損性部件的剩餘壽命。
Entry Deadline:
SIIM-ACR Pneumothorax Segmentation
https://www.kaggle.com/c/siim-acr-pneumothorax-segmentation
Now - Sept 22, 2019 // Host by Kaggle & C-MIMI 2019 // Prize: $30,000
Note: Identify Pneumothorax disease in chest x-rays
Entry Deadline:
Predicting Molecular Properties
https://www.kaggle.com/c/champs-scalar-coupling
Now - August 28, 2019 // Host by Kaggle // Prize: $30,000
Note: Can you measure the magnetic interactions between a pair of atoms?
Entry Deadline:
AIM 2019 image manipulation challenges
http://www.vision.ee.ethz.ch/aim19/
July 17, 2019 - Aug. 30, 2019 // Host by CodaLab & ICCV 2019 // Prize: NaN
Note: Advances in Image Manipulation workshop and challenges on image and video manipulation in conjunction with ICCV 2019.
AIM 2019 image manipulation challenges:
Bokeh Effect Challenge: Track 1 Fidelity
https://competitions.codalab.org/competitions/20156;
Bokeh Effect Challenge: Track 2 Perceptual
https://competitions.codalab.org/competitions/20157;
RAW-to-RGB Mapping Challenge: Track 1 Fidelity
https://competitions.codalab.org/competitions/20158;
RAW-to-RGB Mapping Challenge: Track 2 Perceptual
https://competitions.codalab.org/competitions/20159;
Real World Super-Resolution Challenge: Track 1 Same Domain
https://competitions.codalab.org/competitions/20163;
Real World Super-Resolution Challenge: Track 2 Target Domain
https://competitions.codalab.org/competitions/20164;
Demoireing Challenge: Track 1 Fidelity
https://competitions.codalab.org/competitions/20165;
Demoireing Challenge: Track 2 Perceptual
https://competitions.codalab.org/competitions/20166;
Constrained Super-Resolution Challenge: Track 1 Parameters optimization
https://competitions.codalab.org/competitions/20167;
Constrained Super-Resolution Challenge: Track 2 Inference optimization
https://competitions.codalab.org/competitions/20168;
Constrained Super-Resolution Challenge: Track 3 Fidelity optimization
https://competitions.codalab.org/competitions/20169;
Extreme Super-Resolution Challenge: Track 1 Fidelity
https://competitions.codalab.org/competitions/20235;
Extreme Super-Resolution Challenge: Track 2 Perceptual
https://competitions.codalab.org/competitions/20236;
AIM 2019 video manipulation challenges:
Video Quality Mapping Challenge : Track 1 Supervised
https://competitions.codalab.org/competitions/20246;
Video Quality Mapping Challenge : Track 2 Unsupervised
https://competitions.codalab.org/competitions/20247;
Video Extreme Super-Resolution Challenge: Track 1 Fidelity
https://competitions.codalab.org/competitions/20248;
Video Extreme Super-Resolution Challenge: Track 2 Perceptual
https://competitions.codalab.org/competitions/20249;
Video Temporal Super-Resolution Challenge
https://competitions.codalab.org/competitions/20244;
Entry Deadline:
APTOS 2019 Blindness Detection
https://www.kaggle.com/c/aptos2019-blindness-detection
Now - Sept 5, 2019 // Host by Kaggle & 4th APTOS Symposium // Prize: $50,000
Note: Detect diabetic retinopathy to stop blindness before it's too late
Entry Deadline:
QMUL Surveillance Face Recognition Challenge @ ICCV2019 workshop RLQ
https://qmul-survface.github.io/
27 June - 30 Aug, 2019 // Host by EvalAI & ICCV 2019 // Prize: NaN
Note: The challenge data consists of a set of popular search queries and a fair size set of candidate documents. Challenge participants make a boolean relevant-or-not decision for each query-document pair. Human judgments are used to create labeled training and evaluation data for a subset of the query-document pairs. Evaluation of submissions will be based on the traditional F1 metric, incorporating components of both recall and precision.
Entry Deadline:
“達觀杯”文本智能信息抽取挑戰賽
https://www.biendata.com/competition/datagrand/
06/28 - 08/31 2019 // Host by Biendata // Prize: 七萬七千元
Note: 本次大賽的任務是給定一定數量的標註語料以及海量的未標註語料，在3個字段上做信息抽取任務。
Entry Deadline:
Game of Drones – Competition at NeurIPS 2019
July 1st – Dec. 8th, 2019 // Host by NeurIPS 2019 // Prize: ~12,000USD
Note: Game of Drones is a multi-drone racing tournament conducted in the high-fidelity simulation environment AirSim. Participants will have the choice of three tiers: Planning only, Perception only, or Full Autonomous Racing. The aim is to combine challenges from adversarial planning and real-time perception and to encourage fusing learning- and model-based approaches.
Entry Deadline:
2019之江杯全球人工智能大賽
http://aicup2019.zhejianglab.com/
2019-07-17 至 2019-09-30 // Host by 之江實驗室 // Prize: 大賽總獎金池超過260萬元
Note: 隨着新一輪世界科技革命和產業變革的孕育興起，人工智能已經成爲當前信息技術和未來科技高端發展的重要方向。爲激發廣大科研人員人工智能創業者參與人工智能前沿理論和算法研究的熱情，之江實驗室舉辦2019之江杯全球人工智能大賽，以“以賽引才、以賽促研、以賽興業”爲基本思路，聚焦人工智能“基礎研究”+“產融結合”，促進我國人工智能發展走在世界前列引領科技發展潮流。
視頻描述生成
https://zhejianglab.aliyun.com/entrance/231734/introduction?spm=5176.12281949.1003.1.2b58c341xkeLkZ: 本賽題爲視頻描述（Video Caption）,視頻描述的輸入是一段視頻，輸出是描述視頻主要故事的一段文本。
行人多目標跟蹤
https://zhejianglab.aliyun.com/entrance/231733/introduction?spm=5176.12281949.1003.2.2b58c341xkeLkZ: 主要任務是給定一個圖像序列，找到圖像序列中運動的物體，對目標進行定位，並將不同幀中的同一行人一一對應，記錄其ID，然後給出不同物體的運動軌跡。
零樣本目標檢測
https://zhejianglab.aliyun.com/entrance/231732/introduction?spm=5176.12281949.1003.3.2b58c341xkeLkZ: 零樣本目標檢測（zero-shot object detection）競賽的任務是在已知類別上訓練目標檢測模型，但要求模型能夠用於檢測測試圖片中未知類別的對象。
電商評論觀點挖掘
https://zhejianglab.aliyun.com/entrance/231731/introduction?spm=5176.12281949.1003.4.2b58c341xkeLkZ: 本次品牌評論觀點挖掘的任務是在商品評論中抽取商品屬性特徵和消費者觀點，並確認其情感極性和屬性種類。
Entry Deadline:
Challenge on Deep Learning based Loop Filter for Video Coding
http://challenge.ai.iqiyi.com/detail?raceId=5b112a742a360316a898ff50
May, 25th - May, 31st, 2018 // Host by 愛奇藝|iQIYI & AVS Workgroup // Prize: NaN
Note: The participants are encouraged to investigate neural network based methods (especially convolutional neural networks) with different network structures, in a hope of achieving the best quality with lightest network configuration for a good tradeoff of efficiency and complexity.
Entry Deadline:
CoNLL 2019 Shard Task on Cross-Framework Meaning Representation Parsing
March 6 - November 3, 2019 // Host by CodaLab // Prize: NaN
Note: The 2019 Conference on Computational Language Learning (CoNLL) hosts a shared task (or ‘system bake-off’) on Cross-Framework Meaning Representation Parsing (MRP 2019).
The goal of the task is to advance data-driven parsing into graph-structured representations of sentence meaning.
Entry Deadline:
The 2nd Large-scale Video Object Segmentation Challenge
https://youtube-vos.org/challenge/2019/
May. 20 - Sep. 5 2019 // Host by CodaLab & ICCV 2019 // Prize: NaN
Note: As a continuous effort to push forward the research on video object segmentation tasks, we plan to host a second workshop with a challenge based on the YouTube-VOS dataset, targeting at more diversified problem settings, i.e., we plan to provide two challenge tracks in this workshop.
Track 1: Video Object Segmentation
https://youtube-vos.org/dataset/vos/
Track 2: Video Instance Segmentation
https://youtube-vos.org/dataset/vis/
Entry Deadline:
The 3rd YouTube-8M Video Understanding Challenge
https://www.kaggle.com/c/youtube8m-2019
Now - October 28, 2019 // Host by Kaggle & ICCV 2019 // Prize: $25,000
Note: Temporal localization of topics within video
Entry Deadline:
Automatic Structure Segmentation for Radiotherapy Planning Challenge 2019
https://structseg2019.grand-challenge.org/
June 15 - Oct 1, 2019 // Host by Grand Challenges & MICCAI 2019 // Prize: NaN
Note: The goal of the challenge is to set up tasks for evaluating automatic algorithms on segmentation of organs-at-risk (OAR) and gross target volume (GTV) of tumors of two types of cancers, nasopharynx cancer and lung cancer, for radiation therapy planning. There are four tasks for evaluating the performance of the algorithms. Participants can choose to join all or either tasks according to their interests.
Task 1: Organ-at-risk segmentation from head & neck CT scans.
Task 2: Gross Target Volume segmentation of nasopharynx cancer.
Task 3: Organ-at-risk segmentation from chest CT scans.
Task 4: Gross Target Volume segmentation of lung cancer.
Entry Deadline:
OpenEDS Challenge
https://research.fb.com/programs/openeds-challenge
May 3 - Sep 16, 2019 // Host by EvalAI & Facebook // Prize: $13,000 USD x2
Note: In the absence of accurate gaze labels, we propose to advance the state of the art by carefully designing two challenges that combine human annotation of eye features with unlabeled data. These challenges focus on deeper understanding of the distribution underlying human eye state. We invite ML and CV researchers for participation.
Track-1 Semantic Segmentation challenge
https://evalai.cloudcv.org/web/challenges/challenge-page/353
Track-2 Synthetic Eye Generation challenge
https://evalai.cloudcv.org/web/challenges/challenge-page/354
Entry Deadline:
Exoplanet imaging data challenge
https://exoplanet-imaging-challenge.github.io/
May 16th - Sep 16th, 2019 // Host by CodaLab // Prize: NaN
Note: This competition is composed of two sub-challenges focusing on the two most widely used observing techniques: pupil tracking (angular differential imaging, ADI) and multi-spectral imaging combined with pupil tracking (multi-channel spectral differential imaging, ADI+mSDI).
Entry Deadline:
成語閱讀理解大賽
https://www.biendata.com/competition/idiom/
06/25 - 09/25 2019 // Host by Biendata // Prize: ￥24,000元
Note: 本次競賽將基於選詞填空的任務形式，提供大規模的成語填空訓練語料。在給定若干段文本下，選手需要在提供的候選項中，依次選出填入文本中的空格處最恰當的成語。
Entry Deadline:
Peking University International Competition on Ocular Disease Intelligent Recognition (ODIR-2019)
https://odir2019.grand-challenge.org/
May 18 - Sep 25, 2019 // Host by Grand Challenges & 北京大學 // Prize: 10,00,000 RMB (140,000+ USD)
Note: 北京大學'智慧之眼'國際眼科疾病智能識別競賽
The SG will provide participants with 5,000 structured desensitized ophthalmologic image set of patient's age, sex, binocular color fundus photos and doctors' diagnostic report.
上工醫信將爲參賽者提供5000組包含患者的性別、年齡、雙眼彩色眼底照片和醫生印象報告等的結構化脫敏後眼科的數據集。
The purpose of this challenge is to compare approaches of ophthalmic disease classification in color fundus images. Participant will have to submit classification results of eight categories for all the testing data. For every category, a classification probability (value from 0.0 to 1.0) denotes risk of a patient diagnosed with corresponding category.
該競賽的目的是比較基於彩色眼底圖像進行眼科疾病分類的不同方法。 參與者必須提交所有測試數據集的八個類別的分類結果。 對於每個類別，分類概率（值從0.0到1.0）表示患者被診斷爲具有相應類別的可能性/風險。
Entry Deadline:
NeurIPS 2019 : MineRL Competition
https://www.aicrowd.com/challenges/neurips-2019-minerl-competition
May 10 - Dec 8, 2019 // Host by crowdAI & NeurIPS 2019 // Prize: Nvidia GPUs
Note: The main task of the competition is solving the ObtainDiamond environment. In this environment, the agent begins in a random starting location without any items, and is tasked with obtaining a diamond. This task can only be accomplished by navigating the complex item hierarchy of Minecraft.
Entry Deadline:
Digestive-System Pathological Detection and Segmentation Challenge 2019
https://digestpath2019.grand-challenge.org/
June 14 - Oct 1, 2019 // Host by Grand Challenges & MICCAI 2019 // Prize: NaN
Note: The goal of the challenge is to set up tasks for evaluating automatic algorithms on signet ring cell detection and colonoscopy tissue screening from digestive system pathological images. This will be the first challenge and first public dataset on signet ring cell detection and colonoscopy tissue screening. Releasing the large quantity of expert-level annotations on digestive-system pathological images will substantially advance the research on automatic pathological object detection and lesion segmentation.
Task 1: Signet ring cell detection.
Task 2: Colonoscopy tissue segmentation and classification.
Entry Deadline:
The 2nd China (Hengqin) International University Quantitative Finance Competition
2019-04-19 至 2020-03-21 // Host by 珠海市橫琴新區金融服務中心 // Prize: ￥140萬
Note: 第二屆中國（橫琴）國際高校量化金融大賽
參賽要求 參賽者應根據題目要求，完成一篇包括量化金融策略原理、模型的假設、建立和求解、計算方法的設計、分析和檢驗、模型的改進等方面的書面報告（即答卷）；並在規定競賽期間內，將參賽策略的市場運行進行模擬仿真競賽。根據參賽策略的測試結果（包括樣本內和樣本外）的收益水平及市場風險防範的效果等統一指標打分評比，以市場的標準來決定優劣，評價策略的回測和實盤模擬表現，同時考慮策略邏輯的穩健性和創新性。競賽評獎以策略的合理性、建模的創新性、測試策略的市場適應性及收益風險水平等結果爲主要標準。
Requirements Participants should write a report covering quantitative financial strategy theories 1) Model theoretical hypothesis and description of quantitive model 2) Data analysis 3) Strategy back testing results and performance analysis. According to the requirements of the competition, participants’ strategies will be back tested and paper traded during the required period. Evaluation and scoring will base on unified measurements including return, volatility, max drawdown of the strategies and so on. The determination of merits and evaluation of strategy back test and paper trading performance will be made according to market standards, while the robustness and innovation of the strategic logic will also be taken into consideration. Key criteria will include the rationality of the strategy, the creativeness of the model, the market adaptability of the testing strategy and the level of return and risk.
Entry Deadline:
IEEE-CIS Fraud Detection
https://www.kaggle.com/c/ieee-fraud-detection
Now - October 1, 2019 // Host by Kaggle & IEEE-CIS // Prize: $25,000
Note: Can you detect fraud from customer transactions?
Entry Deadline:
Open Images 2019 - Instance Segmentation
https://www.kaggle.com/c/open-images-2019-instance-segmentation
Now - October 27, 2019 // Host by Kaggle & ICCV 2019 // Prize: $20,000
Note: Outline segmentation masks of objects in images
Entry Deadline:
Open Images 2019
https://storage.googleapis.com/openimages/web/challenge2019.html
Now - Oct 27, 2019 // Host by Kaggle & ICCV 2019 // Prize: $25,000
Note: This year’s Open Images V5 release enabled the second Open Images Challenge to include the following 3 tracks:
Object detection
https://www.kaggle.com/c/open-images-2019-object-detection track for detecting bounding boxes around object instances, relaunched from 2018.
Visual relationship detection track
https://www.kaggle.com/c/open-images-2019-visual-relationship for detecting pairs of objects in particular relations, also relaunched from 2018.
Instance segmentation track [Link to be provided when launched on July 1], brand new for 2019.
Entry Deadline:
Visual Domain Adaptation Challenge (VisDA-2019)
April 9 - Sept. 27, 2019 // Host by CodaLab & ICCV 2019 // Prize: NaN
Note: We are pleased to announce the 2019 Visual Domain Adaptation (VisDA2019) Challenge! It is well known that the success of machine learning methods on visual recognition tasks is highly dependent on access to large labeled datasets. Unfortunately, performance often drops significantly when the model is presented with data from a new deployment domain which it did not see in training, a problem known as dataset shift. The VisDA challenge aims to test domain adaptation methods’ ability to transfer source knowledge and adapt it to novel target domains.
This challenge includes two tracks:
Multi-Source Domain Adaptation Challenge
https://competitions.codalab.org/competitions/22469
Semi-Supervised Domain Adaptation
https://competitions.codalab.org/competitions/22470
Entry Deadline:
AI in RTC-超分辨率圖像質量比較挑戰賽
7月1日-10月23日, 2019 // Host by DC 競賽 // Prize: 100000
Note: 單幀圖像超分辨率近年來備受關注。同樣的圖像，在經過不同超分辨率算法處理後，獲得的圖像質量也有所不同。在這個挑戰中，參賽者需要對100張圖片進行4倍超分辨率處理。比賽最終以PI (perceptual index)指標作爲評判標準，PI值越小，表明圖像質量越高，得分越高，分值高的團隊獲得優勝。
Entry Deadline:
AI in RTC-超分辨率算法性能比較挑戰賽
7月1日-10月23日, 2019 // Host by DC 競賽 // Prize: 100000
Note: 將超分辨算法用於處理實時視頻流時，模型的處理表現與運算性能，是一個兩難的選擇。爲了追求較低複雜度，可能需要犧牲圖像質量；爲了追求較高質量的輸出，導致設備資源佔用過高，產生設備發燙、視頻模糊卡頓等現象。該挑戰主要考察算法模型的性能，參賽者需要對圖像做2倍的超分辨率處理，算法複雜度控制在1GFLOPs之內，我們以SRCNN模型爲baseline, 並採用PSNR、SSIM及運行時間來綜合評估算法的性能，分值高者即獲勝。
Entry Deadline:
Alchemy Contest
5/22 - 9/30, 2019 // Host by CodaLab & Tencent Quantum Lab 騰訊量子實驗室// Prize: total ￥100,000 RMB
Note: The Tencent Quantum Lab has recently introduced a new molecular dataset, called Alchemy, to facilitate the development of new machine learning models useful for chemistry and materials science.
The dataset lists 12 quantum mechanical properties of 130,000+ organic molecules comprising up to 12 heavy atoms (C, N, O, S, F and Cl), sampled from the GDBMedChem database. These properties have been calculated using the open-source computational chemistry program Python-based Simulation of Chemistry Framework (PySCF).
Entry Deadline:
Fashion IQ Challenge
https://competitions.codalab.org/competitions/23391
June 1 - Sept 30, 2019 // Host by CodaLab & ICCV 2019 & Github // Prize: NaN
Note: Fashion IQ is a new dataset we contribute to the research community to facilitate research on natural language based interactive image retrieval
Entry Deadline:
MicroNet Challenge @NeurIPS 2019
https://micronet-challenge.github.io/
June 1, 2018 - Dec 13, 2019 // Host by NeurIPS 2019 // Prize: NaN
Note: The competition consists of three different tasks. Contestants are free to submit entries for one, two, or all three tasks. Contestants are allowed to enter up to three models for each task, but will be ranked according to their top entry in each task. Entries can only be trained on the training data for the task they are entered in. No pre-training, or use of auxiliary data is allowed.
ImageNet Classification
http://image-net.org/index: The de facto standard dataset for image classification. The dataset is composed of 1,281,167 training images and 50,000 development images. Entries are required to achieve 75% top-1 accuracy on the public test set.
CIFAR-100 Classification
https://www.cs.toronto.edu/~kriz/cifar.html: A widely popular image classification dataset of small images. The dataset is composed of 50,000 training images and 10,000 development images. Entries are required to achieve 80% top-1 accuracy on the test set.
WikiText-103 Language Modeling
https://blog.einstein.ai/the-wikitext-long-term-dependency-language-modeling-dataset/: A language modeling dataset that emphasizes long-term dependencies. Entries will perform the standard language modeling task, predicting the next token from the current one. The dataset is composed of 103 million training words, 217 thousand development words, and 245 thousand testing words. Entries should use the standard word-level vocabulary of 267,735 tokens. Entries are required to achieve a word-level perplexity below 35 on the test set.
Entry Deadline:
全球數據資源開發者大賽
2月28-12月28 2019 // Host by 杭州市人民政府 // Prize: TBA
Note:
中國移動專題賽: 賽題一：ETC便民服務羣體挖掘; 賽題二：企業人才結構變化預測;
行業算法賽: 賽題一：樓盤精準推薦模型; 賽題二：社區獨居老人識別與居民用能數據分析; 賽題三：移動辦事服務的用戶行爲預測;
Entry Deadline:
Multi-domain Task-Completion Dialog Challenge [DSTC 8]
https://www.microsoft.com/en-us/research/project/multi-domain-task-completion-dialog-challenge/
June 17 - Oct 6, 2019 // Host by CodaLab & DSTC8 // Prize: NaN
Note: As part of the Eighth Dialog System Technology Challenge (DSTC8), Microsoft Research and Tsinghua University are hosting a track intended to foster progress in two important aspects of dialog systems: dialog complexity and scaling to new domains. For this DSTC8 track, there are two tasks you can compete in (see below). The challenge runs from June 17, 2019 – October 6, 2019.
Participants will build an end-to-end multi-domain dialog system for tourist information desk settings.
Participants will develop fast adaptation methods for building a conversation model that generates appropriate domain-specific user responses to an incomplete dialog history.
Entry Deadline:
Kuzushiji Recognition
https://www.kaggle.com/c/kuzushiji-recognition
Now - October 14, 2019 // Host by Kaggle // Prize: $15,000
Note: Opening the door to a thousand years of Japanese culture
Entry Deadline:
Endoscopic Vision Challenge 2019
https://endovis.grand-challenge.org/Endoscopic_Vision_Challenge/
June 5 - Oct 13, 2019 // Host by Grand Challenges // Prize: NaN
Note: As a vision CAI challenge at MICCAI, our aim is to provide a formal framework for evaluating the current state of the art, gather researchers in the field and provide high quality data with protocols for validating endoscopic vision algorithms.
EndoVis 2019 Sub-challenges:
Surgical Workflow and Skill Analysis
https://endovissub-workflowandskill.grand-challenge.org/
Stereo Correspondence and Reconstruction of Endoscopic Data
https://endovissub2019-scared.grand-challenge.org/
Entry Deadline:
NeurIPS 2019: Learn to Move - Walk Around
http://osim-rl.stanford.edu/docs/nips2019/
June 6 ~ October 27, 2019 // Host by crowdAI & NeurIPS 2019 // Prize: NVIDIA GPU + Travel grant
Note: You are provided with a human musculoskeletal model and a physics-based simulation environment, OpenSim.
There will be three tracks: 1) Best performance, 2) Novel ML solution, and 3) Novel biomechanical solution, where all the winners of each track will be awarded.
Entry Deadline:
Graph Golf: The Order/degree Problem Competition
http://research.nii.ac.jp/graphgolf/
05-13 ~ 11-26, 2019 // Host by CodaLab & CANDAR 2019 // Prize: NaN
Note: Find a graph that has smallest diameter & average shortest path length given an order and a degree.
Graph Golf is an international competition of the order/degree problem since 2015. It is conducted with the goal of making a catalog of smallest-diameter graphs for every order/degree pair. Anyone in the world can take part in the competition by submitting a graph. Outstanding authors are awarded in CANDAR 2019, an international conference held in Nagasaki, Japan, in November 2019.
Entry Deadline:
Traffic4cast -- Traffic Map Movie Forecasting
https://www.iarai.ac.at/traffic4cast/
May 1 - Dec 1, 2019 // Host by NeurIPS 2019 // Prize: ~17,000USD + 2 resea. fellowships up to 12 months + compl. registrations
Note: Predict high resolution traffic flow volume, heading, and speed on a whole city map looking 15 minutes into the future! Kicking off a series of annual competitions, this year's data is based on 100 billion probe points from 3 cities mapped in 5 minute intervals, showing trends across weekdays and seasonal effects. Improved traffic predictions are of great social, environmental, and economic value, while also advancing our general ability to capture the simple implicit rules underlying a complex system and model its future states.
Entry Deadline:
Causality for Climate (C4C)
Jul 31 - Oct 31, 2019 // Host by NeurIPS 2019 // Prize: $10,000USD
Note: A causal understanding of climatic interactions is of high societal relevance from identifying causes of extreme events to process understanding and weather forecasting. This competition comprises a number of multivariate time series datasets featuring major challenges of climate data from time delays and nonlinearity to nonstationarity and selection bias. The competition aims to open up new interdisciplinary research pathways by improving our scientific understanding of Earth’s climate, while also driving method development and benchmarking in the computer science community.
Entry Deadline:
Automated Deep Learning (AutoDL)
Apr 29 - Oct 31, 2019 // Host by NeurIPS 2019 // Prize: ~$10,000USD
Note: The AutoDL challenge aims taking the automate the design of deep learning (DL) methods to solve generic tasks. This is a challenge with “code submission”: machine learning algorithms are trained and tested on a challenge platform on data invisible to the participants. We target applications such as speech, image, video, and text, for which DL methods have had great success recently, to drive the community to work on automating the design of DL models. Raw data will be provided, formatted in a uniform tensor manner, to encourage participants to submit generic algorithms. We will impose restrictions on training time and resources to push the state-of-the-art further. We will provide a large number of pre-formatted public datasets and set up a repository of data exchange to enable meta-learning.
Entry Deadline:
Animal-AI Olympics Competition
January - December, 2019 // Host by EvalAI // Prize: NaN
Note: The Animal-AI Olympics is an AI competition with tests inspired by animal cognition. Participants are given a small environment with just seven different classes of objects that can be placed inside. In each test, the agent needs to retrieve the food in the environment, but to do so there are obstacles to overcome, ramps to climb, boxes to push, and areas that must be avoided. The real challenge is that we don't provide the tests in advance. It's up to you to play with the environment and build interesting setups that can help create an agent that understands how the environment's physics work and the affordances that it has. The final submission should be an agent capable of robust food retrieval behaviour similar to that of many kinds of animals. We know the animals can pass these tests, it's time to see if AI can too. The Animal-AI Olympics is an AI competition with tests inspired by animal cognition. Participants are given a small environment with just seven different classes of objects that can be placed inside. In each test, the agent needs to retrieve the food in the environment, but to do so there are obstacles to overcome, ramps to climb, boxes to push, and areas that must be avoided. The real challenge is that we don't provide the tests in advance. It's up to you to play with the environment and build interesting setups that can help create an agent that understands how the environment's physics work and the affordances that it has. The final submission should be an agent capable of robust food retrieval behaviour similar to that of many kinds of animals. We know the animals can pass these tests, it's time to see if AI can too.
Entry Deadline:
3D Object Detection over HD Maps for Autonomous Cars
https://level5.lyft.com/dataset/
Nov 1 - Nov 7, 2019 // Host by NeurIPS 2019 // Prize: ~17,500USD
Note: Autonomous cars are expected to dramatically redefine the future of transportation. The 3D Perception system of the autonomous car is a critical keystone upon which high level autonomy functions depend. This competition is designed to help advance the state of the art in 3D object detection by focusing research on this topic in the context of autonomous cars, specifically by sharing the full modality of sensor data available to typical autonomous cars, and by providing access to a high fidelity HD map.
Entry Deadline:
Pommerman Year 2: Radio.
TBA – Nov 8, 2019 // Host by NeurIPS 2019 // Prize: ~15,000USD in Google Cloud Credits
Note: Pommerman: Train a team of communicative agents to play Bomberman in a partially observed setting. Compete against other teams.
Entry Deadline:
The Animal-AI Olympics
April - December 2019 // Host by NeurIPS 2019 // Prize: $10,000+
Note: 基於Unity ML Agents Toolkit的動物認知-AI 挑戰
This competition pits our best AI approaches against the animal kingdom to determine if the great successes of AI are now ready to compete with the great successes of evolution at their own game.
Entry Deadline:
EPIC-Kitchens Action Anticipation
https://competitions.codalab.org/competitions/20115
July 3, 2018 - Nov. 22 2019 // Host by CodaLab & EPIC-KITCHENS 2018 // Prize: NaN
Note: The largest dataset in first-person (egocentric) vision; multi-faceted non-scripted recordings in native environments - i.e. the wearers' homes, capturing all daily activities in the kitchen over multiple days.
Action-Recognition Challenge
https://competitions.codalab.org/competitions/20115
Action-Anticipation Challenge
https://competitions.codalab.org/competitions/20071
Object-Detection Challenge
https://competitions.codalab.org/competitions/20111
Entry Deadline:
Geopolitical Forecasting [GF] Challenge 2
https://www.herox.com/IARPAGFChallenge2
April 4, 2018 - Feb. 1, 2020 // Host by Herox // Prize: $250,000
Note: Solvers, whether individuals or teams, will create innovative solutions and methods to produce forecasts to a set of more than 300 questions referred to as Individual Forecasting Problems (IFPs), released regularly over the course of the nine-month Challenge.
Entry Deadline:
ModaNet Fashion Understanding Challenge
https://evalai.cloudcv.org/web/challenges/challenge-page/151
Oct 1, 2018 - Dec 11, 2019 // Host by EvalAI // Prize: NaN
Note: In this challenge, we evaluate model performance for three tasks, object detection, semantic segmentation and instance segmentation. You can participate all tasks or any one of them by choosing which results to be included in your submission.
Entry Deadline:
Live Malaria Challenge
https://researcher.watson.ibm.com/researcher/view_group.php?id=9784
TBA – Dec 11, 2019 // Host by NeurIPS 2019 // Prize: 3 mo. Internship @IBM res. Africa
Note: In the NeurIPS Live Malaria Challenge we are looking for participants to apply machine learning tools to determine novel solutions which could impact malaria policy in Sub Saharan Africa. Specifically, how should combinations of interventions be deployed under budget constraints to impact lives saved and the prevalence of the malaria parasite in a simulated environment.
Entry Deadline:
「二分類算法」提供銀行精準營銷解決方案 | 練習賽
https://www.kesci.com/home/competition/5c234c6626ba91002bfdfdd3
2018年12月29日 - 2019年12月29日 // Host by Kesci // Prize: NaN
Note: 本練習賽的數據，選自UCI機器學習庫中的「銀行營銷數據集(Bank Marketing Data Set)」
Entry Deadline:
SPIE-AAPM-NCI BreastPathQ: Cancer Cellularity Challenge 2019
http://spiechallenges.cloudapp.net/competitions/14
Oct. 15, 2018 - Dec. 31, 2019 // Host by ISBI 2019 & Grand Challenges &cloudapp.net // Prize: NaN
Note: Participants will be tasked to develop an automated method for analyzing histology patches extracted from whole slide images and assign a score reflecting cancer cellularity in each.
Entry Deadline:
Optimizing well-being at work
https://challengedata.ens.fr/challenges/15
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & Oze Energies // Prize: NaN
Note: This challenge proposes to develop machine learning based approaches so as to predict individuals' comfort model using several time series of environmental data obtained from sensors in a large building. The objective is to learn a classifier that uses these time series as inputs to predict the associated comfort class computed as an average of the comfort classes of all individuals in the building, assumed to experience the same environmental conditions.
Entry Deadline:
Drug-related questions classification
https://challengedata.ens.fr/challenges/17
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & Posos // Prize: NaN
Note: The goal of Posos challenge is to predict for each question the associated intent.
Entry Deadline:
Detecting breast cancer metastases
https://challengedata.ens.fr/challenges/18
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & OWKIN // Prize: NaN
Note: The challenge proposed by Owkin is a weakly-supervised binary classification problem : predict whether a patient has any metastase in its lymph node or not, given its slide.
Entry Deadline:
Building Claim Prediction
https://challengedata.ens.fr/challenges/19
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & Generali // Prize: NaN
Note: The goal of the challenge is to predict if a building will have an insurance claim during a certain period. You will have to predict a probability of having at least one claim over the insured period of a building.
Entry Deadline:
Crack the neural code of the brain
https://challengedata.ens.fr/challenges/14
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & GNT ENS // Prize: NaN
Note: The challenge goal is to classify the brain activity state of an animal based on spiking activity patterns of its individual neurons.
Entry Deadline:
Prediction of Sharpe ratio for blends of quantitative strategies
https://challengedata.ens.fr/challenges/13
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & Napoleon X // Prize: NaN
Note: The problem is a prediction challenge that aims at helping the Company to build an optimal blend of quantitative strategies, given a set of such strategies.
Entry Deadline:
Historical consumption regression for electricity supply pricing
https://challengedata.ens.fr/challenges/12
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & BCM Energy // Prize: NaN
Note: The goal of the challenge is to predict, based on the analysis of the correlation of a year of consumption and weather training data, the electricity consumption of two given sites for a test year.
Entry Deadline:
Predict brain deep sleep slow oscillation
https://challengedata.ens.fr/challenges/10
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & Dreem // Prize: NaN
Note: In this dataset, we try to predict whether or not a slow oscillation will be followed by another one in sham condition, i.e. without any stimulation.
Entry Deadline:
Spatiotemporal PM10 concentration prediction
https://challengedata.ens.fr/challenges/7
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & Plume Labs // Prize: NaN
Note: In order to provide air quality forecasts, Plume Labs has built a unique database with readings collected by monitoring stations all over the world. The problem we submit consists in predicting the PM10 readings of some air quality monitoring stations using the readings provided by the monitoring stations nearby as well as urban features.
Entry Deadline:
Dynamic Profile Forecasting
https://challengedata.ens.fr/challenges/6
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & Enedis // Prize: NaN
Note: This challenge is about forecasting dynamic profiles values from their past values and all the components of Enedis’ Half hourly Electrical Balancing.
Entry Deadline:
Solve 2x2x2 Rubik's cube
https://challengedata.ens.fr/challenges/20
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & LumenAI // Prize: NaN
Note: The goal is to design an automatic Rubik's analyzer that estimates the current length of the shortest path to the solution.
Entry Deadline:
Exotic pricing with multidimensional non-linear interpolation
https://challengedata.ens.fr/challenges/9
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & Natixis // Prize: NaN
Note: The purpose of the challenge is to use a training set of 1 million prices to learn how to price a specific type of instruments described by 23 parameters by nonlinear interpolation on these prices.
Entry Deadline:
Screening and Diagnosis of esophageal cancer from in-vivo microscopy images
https://challengedata.ens.fr/challenges/11
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & Mauna Kea Technologies // Prize: NaN
Note: The goal of this challenge is to build an image classifier to assist physicians in the screening and diagnosis of esophageal cancer.
Entry Deadline:
Prediction of daily stock movements on the US market
https://challengedata.ens.fr/challenges/16
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & CFM // Prize: NaN
Note: The goal of this challenge is to predict the sign of the returns (= price change over some time interval) at the end of about 700 days for about 700 stocks.
Entry Deadline:
MEMENTO: MRI White Matter Reconstruction
https://my.vanderbilt.edu/memento/
March 7, 2019 - March 4, 2020 // Host by ISBI 2019 // Prize: NaN
Note: This will be a 2-year challenge.
We aim to host 3 sub-challenges evaluating our current ability to:
(1) predict unseen signal (signal representation; sub-challenge #1)
(2) estimate microstructural measures (signal modeling; sub-challenge #2)
(3) evaluate sensitivity and specificity of potential biomarkers (biomarker evaluation; sub-challenge #3).
Entry Deadline:
Propensity to Fund Mortgages
https://www.crowdanalytix.com/contests/propensity-to-fund-mortgages
25 APR 2019 - 6 JUN 2019 // Host by CrowdANALYTIX // Prize: $10000
Note: Develop a model to predict, given mortgage application information, whether the mortgage will be funded or not.
To predict whether a mortgage will be funded using only this application data, certain leading factors driving the loan’s ultimate status will be identified. Solvers will discover the specific aspects of the dataset that have the greatest impact, and build a model based on this information.
Entry Deadline:
Identify Characters from Product Images
https://www.crowdanalytix.com/contests/identify-characters-from-product-images
12 MAY 2019 - 9 JUL 2019 // Host by CrowdANALYTIX // Prize: NaN
Note: Identify the characters from product image from a list of 42 possible values.
While using machine learning to perform image recognition is currently one of the most popular use cases, in some cases, the existing large-scale models are too broad to be effective for specific business use cases. In this contest we will use a data driven approach to identify the “characters” in an image (product images).
Entry Deadline:
KiTS19 Challenge
https://kits19.grand-challenge.org/
March 15 - August 2, 2019 // Host by Grand Challenges // Prize: NaN
Note: The goal of this challenge is to accelerate the development of reliable kidney and kidney tumor semantic segmentation methodologies.
Entry Deadline:
PAIP 2019 Challenge
https://paip2019.grand-challenge.org/
April 15 - September 2, 2019 // Host by Grand Challenges & MICCAI 2019 // Prize: NaN
Note: The goal of the challenge is to evaluate new and existing algorithms for automated detection of liver cancer in whole-slide images (WSIs). There are two tasks and therefore two leaderboards for evaluating the performance of the algorithms. Participants can choose to join both or either tasks according to their interests.
Task 1: Liver Cancer Segmentation
Task 2: Viable Tumor Burden Estimation
Entry Deadline:
ImageNet Object Localization Challenge
https://www.kaggle.com/c/imagenet-object-localization-challenge
Now - December 31 2029 // Host by Kaggle // Prize: NaN
Note: Identify the objects in images
Entry Deadline:
nocaps
Feb 8, 2019 - Apr 26, 2099 // Host by EvalAI // Prize: NaN
Note: Image captioning models have achieved impressive results on datasets containing limited visual concepts and large amounts of paired image-caption training data. However, if these models are to ever function in the wild, a much larger variety of visual concepts must be learned, ideally from less supervision. To encourage the development of image captioning models that can learn visual concepts from alternative data sources, such as object detection datasets, we present the first large-scale benchmark for this task. Dubbed nocaps, for novel object captioning at scale, our benchmark consists of 166,100 human-generated captions describing 15,100 images from the Open Images validation and test sets. The associated training data consists of COCO image-caption pairs, plus Open Images imagelevel labels and object bounding boxes. Since Open Images contains many more classes than COCO, nearly 400 object classes seen in test images have no or very few associated training captions (hence, nocaps). We extend existing novel object captioning models to establish strong baselines for this benchmark and provide analysis to guide future work on this task.
Entry Deadline:
nuScenes detection challenge
Apr 1, 2019 - Jan 1, 2099 // Host by EvalAI & CVPR 2019 // Prize: NaN
Note: The nuScenes dataset is a large-scale autonomous driving dataset.
Entry Deadline:
Predict Future Sales
https://www.kaggle.com/c/competitive-data-science-predict-future-sales
No deadline // Host by Kaggle // Prize: NaN
Note: Final project for "How to win a data science competition" Coursera course
No Deadline.
Evaluating grammatical error corrections
https://competitions.codalab.org/competitions/15475
Nov. 23, 2016 - Never // Host by CodaLab // Prize: NaN
No Deadline.
TweetQA Competition
July 20, 2019 - Never // Host by CodaLab // Prize: NaN
Note: Unlike other QA datasets like SQuAD in which the answers are extractive, we allow the answers to be abstractive. The task requires model to read a short tweet and a question and outputs a text phrase (does not need to be in the tweet) as the answer.
No Deadline.
Lexical Semantic Change Detection in German
https://competitions.codalab.org/competitions/23563
July 1 - Never // Host by CodaLab // Prize: NaN
Note: Given two corpora Ca and Cb, rank all target words according to their degree of lexical semantic change between Ca and Cb as annotated by human judges. (Higher rank means higher change.)
No Deadline.
YouCook2-BoundingBoxes Video Object Grounding Task
http://youcook2.eecs.umich.edu/
June 24, 2019 - Never // Host by CodaLab & Github // Prize: NaN
Note: YouCook2 is the largest task-oriented, instructional video dataset in the vision community. It contains 2000 long untrimmed videos from 89 cooking recipes; on average, each distinct recipe has 22 videos. The procedure steps for each video are annotated with temporal boundaries and described by imperative English sentences (see the example below).
No Deadline.
Oil Radish Semantic Segmentation and Yield Estimation Challenges
https://competitions.codalab.org/competitions/23386
June 1, 2019 - Never // Host by CodaLab & CVPPP 2019 & CVPR 2019 // Prize: NaN
Note: The challenges associated with the dataset are the Semantic Segmentation challenge and the Yield Estimation challenge. In the Semantic Segmentation challenge, participants must perform pixel-wise classifiction on a subset of the labelled images. In the Yield Estimation challenge, participants must estimate the oil radish yield of same subset of labelled images.
No Deadline.
Challenge: Learning To Drive (L2D)
https://competitions.codalab.org/competitions/23245
June 1, 2019 - Never // Host by CodaLab & ICCV 2019 // Prize: NaN
Note: Challenge participants need to develop driving models that can drive most similar to the human driver that recorded the dataset.
No Deadline.
Mobile age group classification
https://competitions.codalab.org/competitions/22946
May. 17, 2019 - Never // Host by CodaLab // Prize: NaN
Note: This is an EE331 competition leaderboard for Mobile age group classification. It consists of 157K datasamples with 85 various features and age group label (ranging from 1 to 6). The data is splitted into train : validation : test sset with 70 : 20 : 10 ratio.
No Deadline.
Perfect Pitching Simulator
https://fastballs.wordpress.com/category/pitchfx-glossary/
May. 17, 2019 - Never // Host by CodaLab // Prize: NaN
Note: Perfect Pitching Simulator!
No Deadline.
ActivityNet-Entities Object Localization Task
https://github.com/facebookresearch/ActivityNet-Entities
May 7, 2019 - Never // Host by CodaLab & CVPR 2019 // Prize: NaN
Note: ActivityNet-Entities, is based on the video description dataset ActivityNet Captions and augments it with 158k bounding box annotations, each grounding a noun phrase (NP). Here we release the complete set of NP-based annotations as well as the pre-processed object-based annotations.
please see our dataset repo, code repo, and CVPR 2019 oral paper.
No Deadline.
YouCook2 Dense Video Captioning
http://youcook2.eecs.umich.edu/
May 6, 2019 - Never // Host by CodaLab // Prize: NaN
Note: YouCook2 is currently suitable for video-language research, weakly-supervised activity and object recognition in video, common object and action discovery across videos and procedure learning.
No Deadline.
The First Australian Centre for Robotic Vision (ACRV) Challenge
https://competitions.codalab.org/competitions/20940
Dec. 1, 2018 - Never // Host by CodaLab // Prize: NaN
Note: The challenge consists in building an AI agent that can play efficiently and win simplified text-based games using TextWorld.
No Deadline.
TVQA Test Public Evaluation (w/timestamp) Beta
https://competitions.codalab.org/competitions/20686
Nov. 16, 2018 - Never // Host by CodaLab & TVQA // Prize: NaN
Note: This portal is only used for models that used 'ts' (timestamp annotations)
TVQA is a large-scale video QA dataset based on 6 popular TV shows (Friends, The Big Bang Theory, How I Met Your Mother, House M.D., Grey's Anatomy, Castle).
No Deadline.
IWCS-2019 shared task: DRS Parsing
https://competitions.codalab.org/competitions/20220
Feb. 25, 2018 - Never // Host by CodaLab & IWCS-2019 // Prize: NaN
Note: The shared task on DRS parsing will be co-located with IWCS-2019 held in Gothenburg, Sweden on 23-27 May.
No Deadline.
Intuitive Physics Challenge 2019
https://competitions.codalab.org/competitions/20574
Oct. 1, 2018 - Never // Host by CodaLab & IntPhys // Prize: NaN
No Deadline.
SemEval-2019
http://alt.qcri.org/semeval2019/index.php?id=tasks
Now - Never // Host by CodaLab & SemEval-2019 // Prize: NaN
Note:
Frame semantics and semantic parsing:
Task 1: Cross-lingual Semantic Parsing with UCCA
https://competitions.codalab.org/competitions/19160
Task 2: Unsupervised Lexical Semantic Frame Induction
https://competitions.codalab.org/competitions/19159
Opinion, emotion and abusive language detection
Task 3: EmoContext: Contextual Emotion Detection in Text
https://www.humanizing-ai.com/emocontext.html
Task 4: Hyperpartisan News Detection
http://www.webis.de/events/semeval-19
Task 5: HatEval: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter
https://competitions.codalab.org/competitions/19935
Task 6: OffensEval: Identifying and Categorizing Offensive Language in Social Media<\a>
Fact vs fiction
Task 7: RumourEval 2019: Determining Rumour Veracity and Support for Rumours
Task 8: Fact Checking in Community Question Answering Forums
https://competitions.codalab.org/competitions/20022
Information extraction and question answering
Task 9: Suggestion Mining from Online Reviews and Forums
https://competitions.codalab.org/competitions/19955
Task 10: Math Question Answering
https://competitions.codalab.org/competitions/20013
NLP for scientific applications
Task 12: Toponym Resolution in Scientific Papers
https://competitions.codalab.org/competitions/19948
No Deadline.
WiC_competition
https://competitions.codalab.org/competitions/20010
Aug. 18, 2018 - Never // Host by CodaLab // Prize: NaN
Note: You can get all the information and data at https://pilehvar.github.io/wic
No Deadline.
OxUvA Long-Term Tracking Challenge
https://competitions.codalab.org/competitions/19529
July 1, 2018 - Never // Host by CodaLab & ECCV 2018 // Prize: NaN
Note: "We introduce a new video dataset and benchmark to assess single-object tracking algorithms."
No Deadline.
Evergreen: Automatically detect drill core tray outlines in core photography
https://unearthed.solutions/u/competitions/evergreen/get-2-the-core
June 27, 2019 - Never // Host by Unearthed // Prize: NaN
Note: This global online competition invites innovators from around the world to build an algorithm that can determine and map the spatial extents of the core tray and then the individual rows contained within.
No Deadline.
Evergreen: Identify depth measurements in core images
https://unearthed.solutions/u/competitions/evergreen/get-2-core-ii-revenge-depths
June 27, 2019 - Never // Host by Unearthed // Prize: NaN
Note: This is an online competition inviting companies and individuals from around the world to provide a solution that can correctly identify recorded depths within a core photograph.
No Deadline.
Evergreen: Reduce water usage in gold processing through tailings density prediction
https://unearthed.solutions/u/competitions/evergreen/hydrosaver
June 27, 2019 - Never // Host by Unearthed // Prize: NaN
Note: This global online competition invites data scientists and innovators from around the world to develop a prediction model for tailings density (and therefore water consumption) in Newcrest's gold processing operations.
No Deadline.
Lymphocyte Detection
https://lyon19.grand-challenge.org/
under construction // Host by Grand Challenges // Prize: NaN
Note: Dataset contains manual annotations as a ground truth data.
No Deadline.
DRIVE: Digital Retinal Images for Vessel Extraction
https://drive.grand-challenge.org/
No deadline // Host by Grand Challenges // Prize: NaN
Note: The DRIVE database has been established to enable comparative studies on segmentation of blood vessels in retinal images. Develop a system to automatically segment vessels in human retina fundus images.
No Deadline.
PatchCamelyon
https://github.com/basveeling/pcam
No deadline // Host by Grand Challenges // Prize: NaN
Note: The PatchCamelyon benchmark is a new and challenging image classification dataset. It consists of 327.680 color images (96 x 96px) extracted from histopathologic scans of lymph node sections. Each image is annoted with a binary label indicating presence of metastatic tissue. PCam provides a new benchmark for machine learning models: bigger than CIFAR10, smaller than imagenet, trainable on a single GPU.
No Deadline.
The Large Scale Vertebrae Segmentation Challenge (VerSe2019)
https://verse2019.grand-challenge.org/
May 16 - TBA // Host by Grand Challenges // Prize: NaN
Note: Spine or vertebral segmentation is a crucial step in all applications regarding automated quantification of spinal morphology and pathology. With the advent of deep learning, for such a task on computed tomography (CT) scans, a big and varied data is a primary sought-after resource.
Task 1: Vertebra Labelling
Task 2: Vertebra Segmentation
No Deadline.
Vision and Language Navigation
https://evalai.cloudcv.org/web/challenges/challenge-page/97
Mar 13, 2018 - Dec 31, 2099 // Host by EvalAI // Prize: NaN
Note: The challenge requires an autonomous agent to follow a natural language navigation instruction to navigate to a goal location in a previously unseen real-world building.
No Deadline.
VizWiz Challenge 2018
http://vizwiz.org/data/#challenge
Jun 20, 2018 - Jun 22, 2100 // Host by EvalAI // Prize: NaN
Note: Our proposed challenge addresses the following two tasks for this dataset: (1) predict the answer to a visual question and (2) predict whether a visual question cannot be answered.
No Deadline.
SQuAD2.0: The Stanford Question Answering Dataset
https://rajpurkar.github.io/SQuAD-explorer/
No deadline // Host by Stanford NLP Group // Prize: NaN
Note: Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable.
No Deadline.
CoQA: A Conversational Question Answering Challenge
https://stanfordnlp.github.io/coqa/
No deadline // Host by Stanford NLP Group // Prize: NaN
Note: CoQA is a large-scale dataset for building Conversational Question Answering systems. The goal of the CoQA challenge is to measure the ability of machines to understand a text passage and answer a series of interconnected questions that appear in a conversation. CoQA is pronounced as coca.
No Deadline.
Unrestricted Adversarial Examples Challenge
https://github.com/google/unrestricted-adversarial-examples
No deadline // Host by Google AI // Prize: NaN
Note: A community-based challenge to incentivize and measure progress towards the goal of zero confident classification errors in machine learning models.
(不受限對抗樣本挑戰) The project on Github
No Deadline.
The Natural Language Decathlon: A Multitask Challenge for NLP
No deadline // Host by salesforce // Prize: NaN
Note: The Natural Language Decathlon is a multitask challenge that spans ten tasks: question answering (SQuAD), machine translation (IWSLT), summarization (CNN/DM), natural language inference (MNLI), sentiment analysis (SST), semantic role labeling(QA‑SRL), zero-shot relation extraction (QA‑ZRE), goal-oriented dialogue (WOZ), semantic parsing (WikiSQL), and commonsense reasoning (MWSC).