轉於:http://blog.csdn.NET/zb1165048017/article/details/51705020
數學概念部分
座標系,四元數等和3D有關的數學:http://www.cnblogs.com/xiefeifeihu/archive/2009/11/09/1599198.html.
三維旋轉矩陣:http://wenku.baidu.com/view/cc110f88e53a580216fcfe13.html
旋轉矩陣、歐拉角、四元數的比較:http://wenku.baidu.com/view/df9e2133eefdc8d376ee32c4.html
歐拉角和四元數的表示:http://wenku.baidu.com/view/c319fa116c175f0e7cd13791.html
四元數與旋轉:http://blog.sina.com.cn/s/blog_557d254601018dfv.html
B樣條曲線:http://www.cnblogs.com/begtostudy/archive/2010/07/28/1787284.html
非常好的概率統計學習的主頁:http://statistics.zone/
編程語言學習
C#編程視頻:http://lib.csdn.net/base/csharp/resource
OpenGL編程NeHe:http://www.cnblogs.com/irvinow/archive/2009/11/01/1594026.html
OpenGL官網:https://www.opengl.org/
OpenGL“我叫MT“純手工3D動畫製作之1——基礎介紹:http://www.cnblogs.com/KC-Mei/p/4666099.html
跳動的心【非常好玩的代碼】:http://blog.csdn.net/candycat1992/article/details/44040273
跳動的心【原始網站】:https://www.shadertoy.com/view/XsfGRn
繞任意單位軸旋轉矩陣的計算:http://blog.csdn.net/pizi0475/article/details/7932909
3D圖形編程:http://www.verysource.com/category/3d-graphic/
CMU圖形學開設課程簡介:http://www.cnblogs.com/wangze/archive/2010/04/05/1704839.html
bezier曲線控制,B樣條繪製:http://www.cnblogs.com/zhuyaguang/p/4546967.html
opencv2.3在VS2008下的配置:http://blog.csdn.net/moc062066/article/details/6676117
opencv3.1在VS2013下的配置:http://www.th7.cn/Program/cp/201603/773871.shtml
LearnOpenGL簡體中文版:http://bullteacher.com/category/zh_learnopengl_com
OpenGL教程【博客】:http://www.cnblogs.com/zhanglitong
FLTK(fast light toolkit):http://www.seriss.com/people/erco/fltk-videos/fltk-ms-vs-build.html
matlab中plot函數全功能解析:http://blog.sina.com.cn/s/blog_61c0518f0100f0lg.html
matlab圖形着色:http://blog.sina.com.cn/s/blog_758521400102vp1a.html
CGJOY:http://www.cgjoy.com/#
火焰特效:http://blog.sina.com.cn/s/blog_5386fec20101750v.html
8小時學會HTML網頁開發:http://edu.csdn.net/course/detail/535
Android基礎班直播課程視頻回放彙總貼:http://www.kgc.cn/bbs/post/6905.shtml
圖靈機器人:http://www.csdn.net/tag/%E5%9B%BE%E7%81%B5%E6%9C%BA%E5%99%A8%E4%BA%BA
圖靈機器人【官網】:http://www.tuling123.com/
C++編譯各種有趣程序:http://www.demongan.com/content/?343.html
萌碼【學編程的地方】:http://www.mengma.com/volumes
skeletonDrivenAnimation:http://www.pudn.com/downloads466/sourcecode/windows/opengl/detail1956574.html
動捕及計算機視覺
CMU動捕數據庫:http://mocap.cs.cmu.edu/
另一個動捕數據庫【提供了bvh格式】:http://accad.osu.edu/research/mocap/mocap_data.htm
HDM05動捕數據庫:http://resources.mpi-inf.mpg.de/HDM05/index.html#downloads:cuts
另一個提供數據集的地方【還算比較詳細,待研究】:https://sites.google.com/a/cgspeed.com/cgspeed/motion-capture
Gaussian Process Dynamical Models for Human Motion【論文主頁】:http://www.dgp.toronto.edu/~jmwang/gpdm/
基於運動捕捉數據的人體運動編輯技術研究【論文】:http://max.book118.com/html/2014/0422/7841843.shtm
基於數據驅動的實時人體運動控制動畫加界面【論文】:http://www.doc88.com/p-6724472199995.html
運動捕捉數據的處理與編輯技術的研究【論文】:http://www.doc88.com/p-9435446530659.html
動作捕捉ASF/AMC的OpenGL多線程程序:http://download.csdn.net/download/gaojin987/4475156
關節動畫和人體動畫:http://blog.csdn.net/pizi0475/article/details/5458687
機器學習技術在三維人體運動編輯中的研究【論文】:http://www.doc88.com/p-4055135283810.html
運動捕捉及運動編輯技術研究【論文】:http://www.docin.com/p-901093517.html
運動分割Segmenting Motion Capture Data into Distinct Behaviors :http://graphics.cs.cmu.edu/projects/segmentation/
Motion Computing Lab:http://motionlab.kaist.ac.kr/cglab/?page_id=1172
Motion Blending【文章,綜述類】:http://image.diku.dk/projects/media/kristine.slot.07.pdf
Style Translation for Human Motion:http://people.csail.mit.edu/ehsu/work/sig05stf/
Conditional Restricted Boltzmann Machines:http://www.uoguelph.ca/~gwtaylor/thesis/4/
Dynamical Binary Latent Variable Models for 3D Human Pose Tracking:http://www.uoguelph.ca/~gwtaylor/publications/cvpr2010/
Factored Conditional Restricted Boltzmann Machines for Modeling Motion Style:http://www.uoguelph.ca/~gwtaylor/publications/icml2009/
Continuous Character Control with Low-Dimensional Embeddings:http://graphics.stanford.edu/projects/ccclde/
Real-Time Human Action Recognition Based on Depth Motion Maps:http://www.utdallas.edu/~cxc123730/depth_image_action_recognition.html
【序列拼接】CTW:http://www.f-zhou.com/ta_code.html
【序列拼接】ACA:http://www.f-zhou.com/tc_code.html
A Deep Learning Framework For Character Motion Synthesis and Editing:http://www.theorangeduck.com/page/deep-learning-framework-character-motion-synthesis-and-editing
Actions as Space-Time Shapes:http://www.wisdom.weizmann.ac.il/~vision/SpaceTimeActions.html
虛擬人行走的動作融合【論文】:http://www.docin.com/p-407446317.html
Mocap Toolbox:https://www.jyu.fi/hum/laitokset/musiikki/en/research/coe/materials/mocaptoolbox
ASF/AMC格式解讀:http://blog.sina.com.cn/s/blog_13cb8d10e0102vc9c.html
AS skeleton:http://graphics.cs.cmu.edu/nsp/course/15-464/Fall05/assignments/StartupCodeDescription.html
三維人體運動編輯與合成技術綜述:http://wenku.baidu.com/link?url=RPdSQA7QMJ2Sjg7ZG-Ek3xPvrXl8yba1pUXELaRo6KIwI9Y2Clq11tfa3EFrMa-j1KeZBn9rGnQF14AZt7m0p25TE9AtA5CtDNOFiBK9YBW
運動插值【百度文庫】:http://wenku.baidu.com/view/d3c7448d80eb6294dc886c36.html
CVCHINA計算機視覺網址導航:http://www.cvchina.net/hao123/
CVChina計算機視覺論壇:http://www.cvchina.net/catalog.asp?cate=7
cv視覺網【挺多人臉識別代碼】:http://www.cvvision.cn/search/opencv/
AForge.net【C#的計算機視覺庫】:http://www.aforgenet.com/
【人體運動仿真組】中科院:http://humanmotion.ict.ac.cn/PeopleList.html
OpenCV中文網,有教程:http://wiki.opencv.org.cn/index.php/Download#chm.E6.A0.BC.E5.BC.8F.E6.96.87.E6.A1.A3
International Audio Laboratories Erlangen與語音和CV有關,有demo:https://www.audiolabs-erlangen.de/fau/professor/mueller/data
任程的博客運動數據分割:http://www.cnblogs.com/ArenAK/archive/2010/12/19/1910404.html
Xiaowei Zhou運動數據重構:https://fling.seas.upenn.edu/~xiaowz/dynamic/wordpress/
Jovan Popović拼接、骨骼相關:http://homes.cs.washington.edu/~jovan/
CMU的工程主頁,包含動捕方向:http://graphics.cs.cmu.edu/
ASF/AMC數據簡介:http://research.cs.wisc.edu/graphics/Courses/cs-838-1999/Jeff/ASF-AMC.html
機器學習算法
一個牛人的隨筆:http://leftnoteasy.cnblogs.com/
一系列的機器學習算法:http://www.csuldw.com/
SVD奇異值分解:http://blog.csdn.net/wangran51/article/details/7408414
LDA和PCA:http://www.cnblogs.com/LeftNotEasy/archive/2011/01/08/lda-and-pca-machine-learning.html#top
opencv實現聚類算法:http://blog.csdn.net/xlh145/article/details/8862680
SVM支持向量機算法概:http://blog.csdn.net/passball/article/details/7661887
支持向量機通俗導論:http://blog.csdn.net/macyang/article/details/38782399
PCA總結以及matlab實現:http://blog.csdn.net/watkinsong/article/details/8234766
PCA實現人臉檢測:http://blog.csdn.net/mpbchina/article/details/7384425
人臉檢測C++代碼:http://mp.weixin.qq.com/s?__biz=MzI2OTAxNTg2OQ==&mid=209167362&idx=1&sn=db4de1e9aa1bb20c2a219d205031ef0a&scene=20&scene=23&srcid=0303gXglBWuhsGHtPmOqQE8Y#rd
matlab中princomp,pcacov,pcares,barttest四大分析函數的應用:http://blog.sina.com.cn/s/blog_6833a4df0100pwma.html
聚類算法Clustering by fast search and find of density peaks的實現:http://blog.csdn.net/jdplus/article/details/40351541#comments
聚類算法Clustering by fast search and find of density peaks的解讀:http://blog.csdn.net/itplus/article/details/38926837
矩陣特徵值分解與奇異值分解含義解析及應用:http://blog.csdn.net/xiahouzuoxin/article/details/41118351
HMM學習最佳範例:http://www.52nlp.cn/hmm-learn-best-practices-five-forward-algorithm-1
應該掌握的七種迴歸技術:http://www.csdn.net/article/2015-08-19/2825492
最小二乘法:http://blog.csdn.net/lotus___/article/details/20546259
隱馬爾科夫模型攻略:http://blog.csdn.net/pi9nc/article/details/9068043
前向算法Forward algorithm:http://blog.csdn.net/jeiwt/article/details/8076019
最容易理解HMM的文章:http://blog.csdn.net/daringpig/article/details/8072794
Viterbi Algorithm維特比算法【原始資料】:http://www.comp.leeds.ac.uk/roger/HiddenMarkovModels/html_dev/viterbi_algorithm/s1_pg10.html
隱馬爾可夫模型(五)——隱馬爾可夫模型的解碼問題(維特比算法):http://www.cnblogs.com/kaituorensheng/archive/2012/12/04/2802140.html
HMM學習最佳範例七:前向-後向算法:http://blog.csdn.net/u010585135/article/details/43562585
隱馬爾科夫(HMM)模型 前向後向(Forward_backward) 維特比 (viterbi)【代碼解讀】:http://blog.csdn.net/S20091103372/article/details/20400219
隱馬爾科夫模型HMM自學:http://blog.csdn.net/zhqz113144/article/details/9177507
機器學習(Part I)機器學習的種類:http://www.cnblogs.com/ysjxw/archive/2008/04/11/1149002.html
機器學習有監督學習之–迴歸:http://www.cnblogs.com/fanyabo/p/4060498.html
機器學習PartII:監督學習和無監督學習:http://www.cnblogs.com/ysjxw/archive/2008/04/11/1149004.html
斯坦福大學機器學習第二課 “單變量線性迴歸”:http://blog.csdn.net/u011584941/article/details/44961277
第六篇 平穩隨機過程(Stationary Stochastic Processes):http://geodesy.blog.sohu.com/273957996.html
高斯過程之FGPLVM【代碼工具包Faster GP-LVM software in MATLAB】:https://github.com/lawrennd/fgplvm
高斯過程之SGPLVM【代碼工具包Gaussian process latent variable models with shared latent spaces (SGPLVM)】:https://github.com/SheffieldML/SGPLVM
Documentation for GPML Matlab Code version 3.6【高斯過程機器學習matlab代碼】:http://www.gaussianprocess.org/gpml/code/matlab/doc/
如何通俗易懂地理解高斯過程:https://www.zhihu.com/question/46631426
Probabilistic PCA with GPLVM【附帶概率PCA的高斯過程】:http://www.wikicoursenote.com/wiki/Probabilistic_PCA_with_GPLVM
Kernel Methods for Large Scale Representation Learning【核方法處理大範圍表示學習】:http://www.cs.cmu.edu/~andrewgw/pattern/
動態時間規整(DTW):http://blog.csdn.net/liyuefeilong/article/details/45748399
什麼是核函數,作用是什麼:http://www.360doc.com/content/14/0728/15/14106735_397653989.shtml#
機器學習有很多關於核函數的說法,核函數的定義和作用是什麼:https://www.zhihu.com/question/24627666
高斯核函數:http://blog.csdn.net/tianguokaka/article/details/6233369
隨機梯度下降:http://www.cnblogs.com/murongxixi/p/3467365.html
梯度下降與隨機梯度下降:http://blog.csdn.net/u014568921/article/details/44856915
【插值】插值:http://wenku.baidu.com/view/e9c7766b852458fb770b563c.html
【插值】插值:http://wenku.baidu.com/view/da8bcdad4b73f242326c5f79.html?re=view
【插值】第三章 實驗數據的插值1:http://wenku.baidu.com/view/a88e268002d276a200292ebb.html?re=view
【插值】實驗四 數據插值與擬合:http://wenku.baidu.com/view/03ab00e90975f46527d3e141.html?re=view
【插值】拉格朗日插值法 matlab:http://wenku.baidu.com/view/589dbf0c844769eae009ed4a.html
【插值】MATLAB編輯n次拉格朗日函數插值法的程序:http://wenku.baidu.com/view/0f3c6a6b561252d380eb6ed2.html
JMLR【Machine Learning Open Source Software有代碼哦】:http://www.jmlr.org/mloss/
C#.NET開源項目、機器學習、商務智能:http://www.cnblogs.com/asxinyu/archive/2015/08/17/4733741.html
位置敏感哈希Locality-Sensitive Hashing:http://blog.csdn.net/zwwkity/article/details/8559301
UDFDL機器學習教程:http://ufldl.stanford.edu/wiki/index.php/UFLDL%E6%95%99%E7%A8%8B
matlab神經網絡視頻教程:http://video.1kejian.com/video/?70286-0-0.html
機器學習基石 (Machine Learning Foundations)【教授 Hsuan-Tien Lin, 林軒田】:https://class.coursera.org/ntumlone-003/lecture
Probabilistic Models of Cognition:https://probmods.org/
低秩逼近【研究研究能發個論文出來】Low-Rank Matrix Recovery and Completion via Convex Optimization:http://perception.csl.illinois.edu/matrix-rank/introduction.html
【Matlab Audio Processing Examples】音頻處理案例matlab代碼:http://labrosa.ee.columbia.edu/matlab/
機器學習大綱:http://dlib.net/ml.html
【CUDA】深度學習框架:https://developer.nvidia.com/deep-learning-frameworks
【算法組】一個機器學習論壇:http://suanfazu.com/
條件隨機場:http://blog.csdn.net/chlele0105/article/details/14897761
LibSVM:http://www.csie.ntu.edu.tw/~cjlin/libsvm/
Sigmoid函數、極大似然估計、損失函數以、梯度下降以及正則化:https://www.52ml.net/19641.html
深度學習相關
ReLu(Rectified Linear Units)激活函數:http://www.cnblogs.com/neopenx/p/4453161.html
Machine and Deep Learning with Python:https://github.com/szwed/awesome-machine-learning-python
ImageNet Classification with Deep ConvolutionalNeural Networks【文章】:http://www.cs.toronto.edu/~hinton/absps/imagenet.pdf
一個人的博客有關深度學習的幾篇文章:https://www.52ml.net/tags/%E5%90%91%E9%87%8F/page/4
matRBM與受限玻爾茲曼機相關:https://code.google.com/archive/p/matrbm/
theano documentation:http://deeplearning.net/software/theano/#
installation of theano on Windows:http://deeplearning.net/software/theano/install_windows.html#install-windows
百度的paddle主頁:http://www.paddlepaddle.org/cn/index.html
deeplearning tutorial:http://deeplearning.net/tutorial/
WildML(RNN相關):http://www.wildml.com/
UFLDL深度學習(NG執筆):http://ufldl.stanford.edu/tutorial/
deeplearning book:http://www.deeplearningbook.org/
tiny-cnn開源庫的使用(MNIST)【C++Windows版本】:http://blog.csdn.net/fengbingchun/article/details/50573841
Nature重磅:Hinton、LeCun、Bengio三巨頭權威科普深度學習:http://www.dataguru.cn/article-7593-1.html
Deep Learning源代碼收集-持續更新…:http://blog.csdn.net/zouxy09/article/details/11910527
deeplearning documentation:http://deeplearning.net/tutorial/contents.html
windows下安裝caffe【推薦看我前面寫的安裝博客】:http://suanfazu.com/t/windows-caffe/13579
【RNN】RECURRENT NEURAL NETWORKS TUTORIAL, PART 1 – INTRODUCTION TO RNNS:http://www.wildml.com/2015/09/recurrent-neural-networks-tutorial-part-1-introduction-to-rnns/
【RNN】循環神經網絡(RNN, Recurrent Neural Networks)介紹:http://blog.csdn.net/heyongluoyao8/article/details/48636251
【RBM】RBM toolbox:https://github.com/skaae/rbm_toolbox
【RBM】A Beginner’s Tutorial for Restricted Boltzmann Machines:http://deeplearning4j.org/restrictedboltzmannmachine
【RBM】Ruslan Salakhutdinov主頁的一個代碼:http://www.cs.toronto.edu/~rsalakhu/code.html
【RBM】受限玻爾茲曼機:http://blog.csdn.net/pi9nc/article/details/19336535
【RBM】受限玻爾茲曼機(RBM)學習筆記(三)能量函數和概率分佈:http://blog.csdn.net/itplus/article/details/19168989
【RBM】限制玻爾茲曼機(Restricted Boltzmann Machine)學習筆記(一):http://blog.csdn.net/roger__wong/article/details/43374343
【CRBM第一篇】Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations:
地址:http://web.eecs.umich.edu/~honglak/hl_publications.html
【CRBM第二篇】Unsupervised feature learning for audio classification using convolutional deep belief networks.
地址:http://web.eecs.umich.edu/~honglak/hl_publications.html
(提示下載方法,用wget -m)因爲這個數據集貌似有版權問題,不變說太多,嘿嘿
【CNN】CS231n Convolutional Neural Networks for Visual Recognition:http://cs231n.github.io/neural-networks-1/#actfun
【RNN-RBM】Deep learning:四十九(RNN-RBM簡單理解):http://www.cnblogs.com/tornadomeet/p/3439503.html
【caffe解析,以及一些深度學習框架的比較】:http://chenrudan.github.io/blog/2015/11/18/comparethreeopenlib.html
【caffe、tensorFlow、Mxnet對比】:http://chenrudan.github.io/blog/2015/11/18/comparethreeopenlib.html
【DNN】可視化每一層得到的結果:http://yosinski.com/deepvis
【可視化】Visualization of optimal stimuli and invariances for Tiled Convolutional Neural Networks.:http://cs.stanford.edu/~quocle/TCNNweb/index.html
【NVIDIA】GPU學習社區:http://www.gpuworld.cn/
Keep Up With New Trends:http://handong1587.github.io/deep_learning/2016/07/27/keep-up-with-new-trends.html
15 Deep Learning Tutorials:http://www.datasciencecentral.com/profiles/blogs/15-deep-learning-tutorials
Documentation for Deconvolutional Network Toolbox:http://www.matthewzeiler.com/software/DeconvNetToolbox/Documentation/main.html
大牛及其它主頁
CMU計算機科學:http://www.cs.cmu.edu/
劉更代大牛主頁:http://www.cad.zju.edu.cn/home/liugengdai/#papers
Tapas Kanungo’s Software Page【主要研究HMM】:http://www.kanungo.com/software/software.html
南京大學機器人智能與神經計算研究組:http://cs.nju.edu.cn/rinc/SOINN.html
Sheffield Machine Learning Software【github主頁】:https://github.com/SheffieldML?page=2
YARIN GAL【主頁,應該很厲害】:http://mlg.eng.cam.ac.uk/yarin/index.html
YARIN GAL中的一個部分,牽扯到GP和caffe【What My Deep Model Doesn’t Know】:http://mlg.eng.cam.ac.uk/yarin/blog_3d801aa532c1ce.html
Ruslan Salakhutdinov:http://www.cs.toronto.edu/~rsalakhu/
Graham Taylor:http://www.cs.nyu.edu/~gwtaylor/pubs.html
Geoffrey E. Hinton:http://www.cs.toronto.edu/~hinton/還有一個RBM相關的http://www.cs.toronto.edu/~hinton/MatlabForSciencePaper.html
Yoshua Bengio:http://www.iro.umontreal.ca/~bengioy/yoshua_en/index.html
Yann LeCun’s Publications :http://yann.lecun.com/exdb/publis/index.html 主頁是:http://yann.lecun.com/ex/index.html
Neil Lawrence Machine Learning:http://inverseprobability.com/
Aaron Hertzmann:http://www.dgp.toronto.edu/~hertzman/index.html
Sam Roweis:http://www.cs.nyu.edu/~roweis/code.html
Dr徐亦達【在優酷上有機器學習課程哦】:http://www-staff.it.uts.edu.au/~ydxu/index.htm
Alexei (Alyosha) Efros:http://people.eecs.berkeley.edu/~efros/
Roland Memisevic:http://www.iro.umontreal.ca/~memisevr/
Eugene Hsu:http://www.squicky.org/cv/
Wei Liu:http://www.cs.unc.edu/~wliu/
Yangqing Jia (賈揚清)【caffe創始人,你說厲害不】:http://daggerfs.com/
David J Fleet:http://www.cs.toronto.edu/~fleet/
Tomohiko MUKAI:http://mukai-lab.org/mukai/
【此人CRBM研究的比較多】Honglak Lee:http://web.eecs.umich.edu/~honglak/hl_publications.html
【CRBM大牛】Alex Krizhevsky:http://www.cs.utoronto.ca/~kriz/
【CRBM大牛】PENG QI:http://qipeng.me/software/convolutional-rbm.html#reference
【Daniel Holden】http://www.theorangeduck.com/page/all
bharath hariharan:http://home.bharathh.info/
Katerina Fragkiadaki:http://people.eecs.berkeley.edu/~katef/
Matthew Zeiler: http://www.matthewzeiler.com/
【搞檢測的大牛】:RBG:https://people.eecs.berkeley.edu/~rbg/index.html
【CVPR2016】code+paper網址:https://tensortalk.com/?cat=conference-cvpr-2016&t=type-code
SIGGRAPH 2015 papers on the web:http://kesen.realtimerendering.com/sig2015.html
【運動捕捉CMU大牛的主頁】有代碼CTW和GTW:http://www.cs.cmu.edu/~ftorre/codedata.html
【finetuning和遷移學習】好文章:http://mp.weixin.qq.com/s?__biz=MzA3MzI4MjgzMw==&mid=2650718634&idx=1&sn=1220e691541c34281c64655a01793cb0&scene=0#rd
微軟研究院劉世霞,做了CNN的可視化,非常好:http://shixialiu.com/
幾個學習網站
csdn:http://www.csdn.net/
我愛自然語言處理NLP:http://www.52nlp.cn/
Coursera:https://www.coursera.org/
matlab中文論壇:http://www.ilovematlab.cn/forum.php
gitxiv【有論文有代碼極力推薦】:http://gitxiv.com/
tensortalk【另一個有代碼和論文的地方】:https://tensortalk.com/?t=type-code
csdn的公開課:http://edu.csdn.net/huiyiCourse/index
Publications【一堆論文,部分有代碼】:https://www.cs.toronto.edu/~ilya/pubs/
Jack M. Wang:http://www.dgp.toronto.edu/~jmwang/
【天津大學深度學習一線實戰研討班乾貨總結與資源下載】:http://datasci.tju.edu.cn/data/index1?sukey=3997c0719f1515200399a26940a285f019a686a850fcc3d81290e00ce57e15e915fbabfbca74f113889c6a7bc0ce4a23
【valse】教學視頻:http://vision.ouc.edu.cn/valse/
機器之心:http://www.jiqizhixin.com/insights
其它
代碼託管網站【碼雲】:http://git.oschina.net/
代碼素材網:http://www.16sucai.com/daima/
百度、騰訊、搜狐、360等產品職位筆試智力題分析:http://blog.csdn.net/foreverdengwei/article/details/7683975#comments
百度 機器學習/數據挖掘 一面 被淘汰 記:http://blog.csdn.net/mpbchina/article/details/8018005
常見面試之機器學習算法思想簡單梳理:http://blog.csdn.net/jirongzi_cs2011/article/details/15720447
NLPjob【找自然語言處理工作】:http://www.nlpjob.com/jobs/machine-learning/
Pro Git v2中文版:http://wiki.jikexueyuan.com/project/pro-git-two/
測測IQ:http://iqtest.dk/main.swf
CVPR 2015 papers:http://cs.stanford.edu/people/karpathy/cvpr2015papers/
CVPR2015:http://techtalks.tv/cvpr/2015/?url_type=39&object_type=webpage&pos=1
繪製流程圖:https://www.processon.com/diagrams
Engineering Village【找論文】:https://www.engineeringvillage.com/home.url?acw=
手寫識別數據庫THE MNIST DATABASE of handwritten digits:http://yann.lecun.com/exdb/mnist/
中國智能網:http://www.5iai.com/
SIGGRAPH 2016 papers on the web:http://www.kesen.realtimerendering.com/sig2016-changelog.html
windows下的WGET下載東西:http://www.interlog.com/~tcharron/wgetwin.html
WGET各參數介紹:http://blog.csdn.net/cnki_ok/article/details/7921239
【PPT】模板素材網站:http://www.officeplus.cn/p/94/102194.shtml
Texlive簡潔教程:http://liam0205.me/2014/09/08/latex-introduction/
數學概念部分
座標系,四元數等和3D有關的數學:http://www.cnblogs.com/xiefeifeihu/archive/2009/11/09/1599198.html.
三維旋轉矩陣:http://wenku.baidu.com/view/cc110f88e53a580216fcfe13.html
旋轉矩陣、歐拉角、四元數的比較:http://wenku.baidu.com/view/df9e2133eefdc8d376ee32c4.html
歐拉角和四元數的表示:http://wenku.baidu.com/view/c319fa116c175f0e7cd13791.html
四元數與旋轉:http://blog.sina.com.cn/s/blog_557d254601018dfv.html
B樣條曲線:http://www.cnblogs.com/begtostudy/archive/2010/07/28/1787284.html
非常好的概率統計學習的主頁:http://statistics.zone/
編程語言學習
C#編程視頻:http://lib.csdn.net/base/csharp/resource
OpenGL編程NeHe:http://www.cnblogs.com/irvinow/archive/2009/11/01/1594026.html
OpenGL官網:https://www.opengl.org/
OpenGL“我叫MT“純手工3D動畫製作之1——基礎介紹:http://www.cnblogs.com/KC-Mei/p/4666099.html
跳動的心【非常好玩的代碼】:http://blog.csdn.net/candycat1992/article/details/44040273
跳動的心【原始網站】:https://www.shadertoy.com/view/XsfGRn
繞任意單位軸旋轉矩陣的計算:http://blog.csdn.net/pizi0475/article/details/7932909
3D圖形編程:http://www.verysource.com/category/3d-graphic/
CMU圖形學開設課程簡介:http://www.cnblogs.com/wangze/archive/2010/04/05/1704839.html
bezier曲線控制,B樣條繪製:http://www.cnblogs.com/zhuyaguang/p/4546967.html
opencv2.3在VS2008下的配置:http://blog.csdn.net/moc062066/article/details/6676117
opencv3.1在VS2013下的配置:http://www.th7.cn/Program/cp/201603/773871.shtml
LearnOpenGL簡體中文版:http://bullteacher.com/category/zh_learnopengl_com
OpenGL教程【博客】:http://www.cnblogs.com/zhanglitong
FLTK(fast light toolkit):http://www.seriss.com/people/erco/fltk-videos/fltk-ms-vs-build.html
matlab中plot函數全功能解析:http://blog.sina.com.cn/s/blog_61c0518f0100f0lg.html
matlab圖形着色:http://blog.sina.com.cn/s/blog_758521400102vp1a.html
CGJOY:http://www.cgjoy.com/#
火焰特效:http://blog.sina.com.cn/s/blog_5386fec20101750v.html
8小時學會HTML網頁開發:http://edu.csdn.net/course/detail/535
Android基礎班直播課程視頻回放彙總貼:http://www.kgc.cn/bbs/post/6905.shtml
圖靈機器人:http://www.csdn.net/tag/%E5%9B%BE%E7%81%B5%E6%9C%BA%E5%99%A8%E4%BA%BA
圖靈機器人【官網】:http://www.tuling123.com/
C++編譯各種有趣程序:http://www.demongan.com/content/?343.html
萌碼【學編程的地方】:http://www.mengma.com/volumes
skeletonDrivenAnimation:http://www.pudn.com/downloads466/sourcecode/windows/opengl/detail1956574.html
動捕及計算機視覺
CMU動捕數據庫:http://mocap.cs.cmu.edu/
另一個動捕數據庫【提供了bvh格式】:http://accad.osu.edu/research/mocap/mocap_data.htm
HDM05動捕數據庫:http://resources.mpi-inf.mpg.de/HDM05/index.html#downloads:cuts
另一個提供數據集的地方【還算比較詳細,待研究】:https://sites.google.com/a/cgspeed.com/cgspeed/motion-capture
Gaussian Process Dynamical Models for Human Motion【論文主頁】:http://www.dgp.toronto.edu/~jmwang/gpdm/
基於運動捕捉數據的人體運動編輯技術研究【論文】:http://max.book118.com/html/2014/0422/7841843.shtm
基於數據驅動的實時人體運動控制動畫加界面【論文】:http://www.doc88.com/p-6724472199995.html
運動捕捉數據的處理與編輯技術的研究【論文】:http://www.doc88.com/p-9435446530659.html
動作捕捉ASF/AMC的OpenGL多線程程序:http://download.csdn.net/download/gaojin987/4475156
關節動畫和人體動畫:http://blog.csdn.net/pizi0475/article/details/5458687
機器學習技術在三維人體運動編輯中的研究【論文】:http://www.doc88.com/p-4055135283810.html
運動捕捉及運動編輯技術研究【論文】:http://www.docin.com/p-901093517.html
運動分割Segmenting Motion Capture Data into Distinct Behaviors :http://graphics.cs.cmu.edu/projects/segmentation/
Motion Computing Lab:http://motionlab.kaist.ac.kr/cglab/?page_id=1172
Motion Blending【文章,綜述類】:http://image.diku.dk/projects/media/kristine.slot.07.pdf
Style Translation for Human Motion:http://people.csail.mit.edu/ehsu/work/sig05stf/
Conditional Restricted Boltzmann Machines:http://www.uoguelph.ca/~gwtaylor/thesis/4/
Dynamical Binary Latent Variable Models for 3D Human Pose Tracking:http://www.uoguelph.ca/~gwtaylor/publications/cvpr2010/
Factored Conditional Restricted Boltzmann Machines for Modeling Motion Style:http://www.uoguelph.ca/~gwtaylor/publications/icml2009/
Continuous Character Control with Low-Dimensional Embeddings:http://graphics.stanford.edu/projects/ccclde/
Real-Time Human Action Recognition Based on Depth Motion Maps:http://www.utdallas.edu/~cxc123730/depth_image_action_recognition.html
【序列拼接】CTW:http://www.f-zhou.com/ta_code.html
【序列拼接】ACA:http://www.f-zhou.com/tc_code.html
A Deep Learning Framework For Character Motion Synthesis and Editing:http://www.theorangeduck.com/page/deep-learning-framework-character-motion-synthesis-and-editing
Actions as Space-Time Shapes:http://www.wisdom.weizmann.ac.il/~vision/SpaceTimeActions.html
虛擬人行走的動作融合【論文】:http://www.docin.com/p-407446317.html
Mocap Toolbox:https://www.jyu.fi/hum/laitokset/musiikki/en/research/coe/materials/mocaptoolbox
ASF/AMC格式解讀:http://blog.sina.com.cn/s/blog_13cb8d10e0102vc9c.html
AS skeleton:http://graphics.cs.cmu.edu/nsp/course/15-464/Fall05/assignments/StartupCodeDescription.html
三維人體運動編輯與合成技術綜述:http://wenku.baidu.com/link?url=RPdSQA7QMJ2Sjg7ZG-Ek3xPvrXl8yba1pUXELaRo6KIwI9Y2Clq11tfa3EFrMa-j1KeZBn9rGnQF14AZt7m0p25TE9AtA5CtDNOFiBK9YBW
運動插值【百度文庫】:http://wenku.baidu.com/view/d3c7448d80eb6294dc886c36.html
CVCHINA計算機視覺網址導航:http://www.cvchina.net/hao123/
CVChina計算機視覺論壇:http://www.cvchina.net/catalog.asp?cate=7
cv視覺網【挺多人臉識別代碼】:http://www.cvvision.cn/search/opencv/
AForge.net【C#的計算機視覺庫】:http://www.aforgenet.com/
【人體運動仿真組】中科院:http://humanmotion.ict.ac.cn/PeopleList.html
OpenCV中文網,有教程:http://wiki.opencv.org.cn/index.php/Download#chm.E6.A0.BC.E5.BC.8F.E6.96.87.E6.A1.A3
International Audio Laboratories Erlangen與語音和CV有關,有demo:https://www.audiolabs-erlangen.de/fau/professor/mueller/data
任程的博客運動數據分割:http://www.cnblogs.com/ArenAK/archive/2010/12/19/1910404.html
Xiaowei Zhou運動數據重構:https://fling.seas.upenn.edu/~xiaowz/dynamic/wordpress/
Jovan Popović拼接、骨骼相關:http://homes.cs.washington.edu/~jovan/
CMU的工程主頁,包含動捕方向:http://graphics.cs.cmu.edu/
ASF/AMC數據簡介:http://research.cs.wisc.edu/graphics/Courses/cs-838-1999/Jeff/ASF-AMC.html
機器學習算法
一個牛人的隨筆:http://leftnoteasy.cnblogs.com/
一系列的機器學習算法:http://www.csuldw.com/
SVD奇異值分解:http://blog.csdn.net/wangran51/article/details/7408414
LDA和PCA:http://www.cnblogs.com/LeftNotEasy/archive/2011/01/08/lda-and-pca-machine-learning.html#top
opencv實現聚類算法:http://blog.csdn.net/xlh145/article/details/8862680
SVM支持向量機算法概:http://blog.csdn.net/passball/article/details/7661887
支持向量機通俗導論:http://blog.csdn.net/macyang/article/details/38782399
PCA總結以及matlab實現:http://blog.csdn.net/watkinsong/article/details/8234766
PCA實現人臉檢測:http://blog.csdn.net/mpbchina/article/details/7384425
人臉檢測C++代碼:http://mp.weixin.qq.com/s?__biz=MzI2OTAxNTg2OQ==&mid=209167362&idx=1&sn=db4de1e9aa1bb20c2a219d205031ef0a&scene=20&scene=23&srcid=0303gXglBWuhsGHtPmOqQE8Y#rd
matlab中princomp,pcacov,pcares,barttest四大分析函數的應用:http://blog.sina.com.cn/s/blog_6833a4df0100pwma.html
聚類算法Clustering by fast search and find of density peaks的實現:http://blog.csdn.net/jdplus/article/details/40351541#comments
聚類算法Clustering by fast search and find of density peaks的解讀:http://blog.csdn.net/itplus/article/details/38926837
矩陣特徵值分解與奇異值分解含義解析及應用:http://blog.csdn.net/xiahouzuoxin/article/details/41118351
HMM學習最佳範例:http://www.52nlp.cn/hmm-learn-best-practices-five-forward-algorithm-1
應該掌握的七種迴歸技術:http://www.csdn.net/article/2015-08-19/2825492
最小二乘法:http://blog.csdn.net/lotus___/article/details/20546259
隱馬爾科夫模型攻略:http://blog.csdn.net/pi9nc/article/details/9068043
前向算法Forward algorithm:http://blog.csdn.net/jeiwt/article/details/8076019
最容易理解HMM的文章:http://blog.csdn.net/daringpig/article/details/8072794
Viterbi Algorithm維特比算法【原始資料】:http://www.comp.leeds.ac.uk/roger/HiddenMarkovModels/html_dev/viterbi_algorithm/s1_pg10.html
隱馬爾可夫模型(五)——隱馬爾可夫模型的解碼問題(維特比算法):http://www.cnblogs.com/kaituorensheng/archive/2012/12/04/2802140.html
HMM學習最佳範例七:前向-後向算法:http://blog.csdn.net/u010585135/article/details/43562585
隱馬爾科夫(HMM)模型 前向後向(Forward_backward) 維特比 (viterbi)【代碼解讀】:http://blog.csdn.net/S20091103372/article/details/20400219
隱馬爾科夫模型HMM自學:http://blog.csdn.net/zhqz113144/article/details/9177507
機器學習(Part I)機器學習的種類:http://www.cnblogs.com/ysjxw/archive/2008/04/11/1149002.html
機器學習有監督學習之–迴歸:http://www.cnblogs.com/fanyabo/p/4060498.html
機器學習PartII:監督學習和無監督學習:http://www.cnblogs.com/ysjxw/archive/2008/04/11/1149004.html
斯坦福大學機器學習第二課 “單變量線性迴歸”:http://blog.csdn.net/u011584941/article/details/44961277
第六篇 平穩隨機過程(Stationary Stochastic Processes):http://geodesy.blog.sohu.com/273957996.html
高斯過程之FGPLVM【代碼工具包Faster GP-LVM software in MATLAB】:https://github.com/lawrennd/fgplvm
高斯過程之SGPLVM【代碼工具包Gaussian process latent variable models with shared latent spaces (SGPLVM)】:https://github.com/SheffieldML/SGPLVM
Documentation for GPML Matlab Code version 3.6【高斯過程機器學習matlab代碼】:http://www.gaussianprocess.org/gpml/code/matlab/doc/
如何通俗易懂地理解高斯過程:https://www.zhihu.com/question/46631426
Probabilistic PCA with GPLVM【附帶概率PCA的高斯過程】:http://www.wikicoursenote.com/wiki/Probabilistic_PCA_with_GPLVM
Kernel Methods for Large Scale Representation Learning【核方法處理大範圍表示學習】:http://www.cs.cmu.edu/~andrewgw/pattern/
動態時間規整(DTW):http://blog.csdn.net/liyuefeilong/article/details/45748399
什麼是核函數,作用是什麼:http://www.360doc.com/content/14/0728/15/14106735_397653989.shtml#
機器學習有很多關於核函數的說法,核函數的定義和作用是什麼:https://www.zhihu.com/question/24627666
高斯核函數:http://blog.csdn.net/tianguokaka/article/details/6233369
隨機梯度下降:http://www.cnblogs.com/murongxixi/p/3467365.html
梯度下降與隨機梯度下降:http://blog.csdn.net/u014568921/article/details/44856915
【插值】插值:http://wenku.baidu.com/view/e9c7766b852458fb770b563c.html
【插值】插值:http://wenku.baidu.com/view/da8bcdad4b73f242326c5f79.html?re=view
【插值】第三章 實驗數據的插值1:http://wenku.baidu.com/view/a88e268002d276a200292ebb.html?re=view
【插值】實驗四 數據插值與擬合:http://wenku.baidu.com/view/03ab00e90975f46527d3e141.html?re=view
【插值】拉格朗日插值法 matlab:http://wenku.baidu.com/view/589dbf0c844769eae009ed4a.html
【插值】MATLAB編輯n次拉格朗日函數插值法的程序:http://wenku.baidu.com/view/0f3c6a6b561252d380eb6ed2.html
JMLR【Machine Learning Open Source Software有代碼哦】:http://www.jmlr.org/mloss/
C#.NET開源項目、機器學習、商務智能:http://www.cnblogs.com/asxinyu/archive/2015/08/17/4733741.html
位置敏感哈希Locality-Sensitive Hashing:http://blog.csdn.net/zwwkity/article/details/8559301
UDFDL機器學習教程:http://ufldl.stanford.edu/wiki/index.php/UFLDL%E6%95%99%E7%A8%8B
matlab神經網絡視頻教程:http://video.1kejian.com/video/?70286-0-0.html
機器學習基石 (Machine Learning Foundations)【教授 Hsuan-Tien Lin, 林軒田】:https://class.coursera.org/ntumlone-003/lecture
Probabilistic Models of Cognition:https://probmods.org/
低秩逼近【研究研究能發個論文出來】Low-Rank Matrix Recovery and Completion via Convex Optimization:http://perception.csl.illinois.edu/matrix-rank/introduction.html
【Matlab Audio Processing Examples】音頻處理案例matlab代碼:http://labrosa.ee.columbia.edu/matlab/
機器學習大綱:http://dlib.net/ml.html
【CUDA】深度學習框架:https://developer.nvidia.com/deep-learning-frameworks
【算法組】一個機器學習論壇:http://suanfazu.com/
條件隨機場:http://blog.csdn.net/chlele0105/article/details/14897761
LibSVM:http://www.csie.ntu.edu.tw/~cjlin/libsvm/
Sigmoid函數、極大似然估計、損失函數以、梯度下降以及正則化:https://www.52ml.net/19641.html
深度學習相關
大牛及其它主頁
CMU計算機科學:http://www.cs.cmu.edu/
劉更代大牛主頁:http://www.cad.zju.edu.cn/home/liugengdai/#papers
Tapas Kanungo’s Software Page【主要研究HMM】:http://www.kanungo.com/software/software.html
南京大學機器人智能與神經計算研究組:http://cs.nju.edu.cn/rinc/SOINN.html
Sheffield Machine Learning Software【github主頁】:https://github.com/SheffieldML?page=2
YARIN GAL【主頁,應該很厲害】:http://mlg.eng.cam.ac.uk/yarin/index.html
YARIN GAL中的一個部分,牽扯到GP和caffe【What My Deep Model Doesn’t Know】:http://mlg.eng.cam.ac.uk/yarin/blog_3d801aa532c1ce.html
Ruslan Salakhutdinov:http://www.cs.toronto.edu/~rsalakhu/
Graham Taylor:http://www.cs.nyu.edu/~gwtaylor/pubs.html
Geoffrey E. Hinton:http://www.cs.toronto.edu/~hinton/還有一個RBM相關的http://www.cs.toronto.edu/~hinton/MatlabForSciencePaper.html
Yoshua Bengio:http://www.iro.umontreal.ca/~bengioy/yoshua_en/index.html
Yann LeCun’s Publications :http://yann.lecun.com/exdb/publis/index.html 主頁是:http://yann.lecun.com/ex/index.html
Neil Lawrence Machine Learning:http://inverseprobability.com/
Aaron Hertzmann:http://www.dgp.toronto.edu/~hertzman/index.html
Sam Roweis:http://www.cs.nyu.edu/~roweis/code.html
Dr徐亦達【在優酷上有機器學習課程哦】:http://www-staff.it.uts.edu.au/~ydxu/index.htm
Alexei (Alyosha) Efros:http://people.eecs.berkeley.edu/~efros/
Roland Memisevic:http://www.iro.umontreal.ca/~memisevr/
Eugene Hsu:http://www.squicky.org/cv/
Wei Liu:http://www.cs.unc.edu/~wliu/
Yangqing Jia (賈揚清)【caffe創始人,你說厲害不】:http://daggerfs.com/
David J Fleet:http://www.cs.toronto.edu/~fleet/
Tomohiko MUKAI:http://mukai-lab.org/mukai/
【此人CRBM研究的比較多】Honglak Lee:http://web.eecs.umich.edu/~honglak/hl_publications.html
【CRBM大牛】Alex Krizhevsky:http://www.cs.utoronto.ca/~kriz/
【CRBM大牛】PENG QI:http://qipeng.me/software/convolutional-rbm.html#reference
【Daniel Holden】http://www.theorangeduck.com/page/all
bharath hariharan:http://home.bharathh.info/
Katerina Fragkiadaki:http://people.eecs.berkeley.edu/~katef/
Matthew Zeiler: http://www.matthewzeiler.com/
【搞檢測的大牛】:RBG:https://people.eecs.berkeley.edu/~rbg/index.html
【CVPR2016】code+paper網址:https://tensortalk.com/?cat=conference-cvpr-2016&t=type-code
SIGGRAPH 2015 papers on the web:http://kesen.realtimerendering.com/sig2015.html
【運動捕捉CMU大牛的主頁】有代碼CTW和GTW:http://www.cs.cmu.edu/~ftorre/codedata.html
【finetuning和遷移學習】好文章:http://mp.weixin.qq.com/s?__biz=MzA3MzI4MjgzMw==&mid=2650718634&idx=1&sn=1220e691541c34281c64655a01793cb0&scene=0#rd
微軟研究院劉世霞,做了CNN的可視化,非常好:http://shixialiu.com/
幾個學習網站
csdn:http://www.csdn.net/
我愛自然語言處理NLP:http://www.52nlp.cn/
Coursera:https://www.coursera.org/
matlab中文論壇:http://www.ilovematlab.cn/forum.php
gitxiv【有論文有代碼極力推薦】:http://gitxiv.com/
tensortalk【另一個有代碼和論文的地方】:https://tensortalk.com/?t=type-code
csdn的公開課:http://edu.csdn.net/huiyiCourse/index
Publications【一堆論文,部分有代碼】:https://www.cs.toronto.edu/~ilya/pubs/
Jack M. Wang:http://www.dgp.toronto.edu/~jmwang/
【天津大學深度學習一線實戰研討班乾貨總結與資源下載】:http://datasci.tju.edu.cn/data/index1?sukey=3997c0719f1515200399a26940a285f019a686a850fcc3d81290e00ce57e15e915fbabfbca74f113889c6a7bc0ce4a23
【valse】教學視頻:http://vision.ouc.edu.cn/valse/
機器之心:http://www.jiqizhixin.com/insights
其它
代碼託管網站【碼雲】:http://git.oschina.net/
代碼素材網:http://www.16sucai.com/daima/
百度、騰訊、搜狐、360等產品職位筆試智力題分析:http://blog.csdn.net/foreverdengwei/article/details/7683975#comments
百度 機器學習/數據挖掘 一面 被淘汰 記:http://blog.csdn.net/mpbchina/article/details/8018005
常見面試之機器學習算法思想簡單梳理:http://blog.csdn.net/jirongzi_cs2011/article/details/15720447
NLPjob【找自然語言處理工作】:http://www.nlpjob.com/jobs/machine-learning/
Pro Git v2中文版:http://wiki.jikexueyuan.com/project/pro-git-two/
測測IQ:http://iqtest.dk/main.swf
CVPR 2015 papers:http://cs.stanford.edu/people/karpathy/cvpr2015papers/
CVPR2015:http://techtalks.tv/cvpr/2015/?url_type=39&object_type=webpage&pos=1
繪製流程圖:https://www.processon.com/diagrams
Engineering Village【找論文】:https://www.engineeringvillage.com/home.url?acw=
手寫識別數據庫THE MNIST DATABASE of handwritten digits:http://yann.lecun.com/exdb/mnist/
中國智能網:http://www.5iai.com/
SIGGRAPH 2016 papers on the web:http://www.kesen.realtimerendering.com/sig2016-changelog.html
windows下的WGET下載東西:http://www.interlog.com/~tcharron/wgetwin.html
WGET各參數介紹:http://blog.csdn.net/cnki_ok/article/details/7921239
【PPT】模板素材網站:http://www.officeplus.cn/p/94/102194.shtml
Texlive簡潔教程:http://liam0205.me/2014/09/08/latex-introduction/