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微机视觉牛人博客和代码汇总

2019年1月2日 - 赌博网站开户送88元

各样做过仍然正在做讨论工作的人都会关切一些融洽认为有价值的、活跃的研讨组和个体的主页,关注他们的主页有时候比盲目标去探寻一些杂文有用多了,大牛的要么活跃的探究者主页往往提供了他们的新式研商线索,顺便还可八一晃各位大牛的经验,对于自身这么的小菜鸟来说最最实用的是偶发可以找到源码,很多时候光看小说是理不清思路的。

1 牛人Homepages(随意排序,不分先后):

1.USC Computer Vision
Group
:南加大,多目的跟踪/检测等;

2.ETHZ Computer Vision
Laboratory
:巴塞罗那联邦外贸大学,非洲最好的多少个CV/ML探讨机构;

3.Helmut Grabner:Online
Boosting and Vision的作者,tracking by online feature
selection的初期经典,貌似现在不是很活跃了,跑去创业了;

4.Robert T.
Collins
:PSU,也是跟踪界的大牛;

5.Ying
Wu
:U.S.西武大学,华人学者中的翘楚;

6.Junsong
Yuan
:NTU,下面Wu老师的学童;

7.James W.
Davis
:德克萨斯州立,录像监控;

8. The Australian Centre for Visual
Technologies
:阿德莱德(Adelaide)大学的CV组,近日也是exceedingly
active & fruitful;

赌博网站开户送88元,9.Chunhua
Shen
:属地方的ACVT组,最近丰富活跃;

10.Xi
Li
:同属ACVT,从前是中科院的PHD,跟踪方面的舆论很多,有理论深度;

11.Haibin
Ling
:天普高校,L1-Tracker及后续扩充,源码分享;

12.Learning, Recognition, and
Surveillance
:奥地利 TU
Graz,在线学习,跟踪/检测等,active!源码分享;

13.Statistical Visual Computing
Laboratory
:UCSD,光听名字就很学术吧,Saliency研究很著名;

14.David
Ross
:华沙高校,IVT的作者,跟踪中Generative表观的经文中的经典,提供源码,IVT的代码结构被新兴成千上万人引用,值得一读;

15.EPFL, Computer Vision
Laboratory
:瓜达拉哈拉理工的高校,和方面的的ETHZ CV
lab同样是北美洲最好的CV探讨大组;

16.Jamie
Shotton
:属微软巴黎高等师范研讨主题,Decision/Regression
Forests

17.Sinisa
Todorovic
:路易斯安那州立,行为分析等;

18.Shi Jianbo:大名鼎鼎的Good Feature
to Track作者,近来大势作为分析和多目的跟踪等;

19.Shai
Avidan
:圣地亚哥大学,大牛级,可算是Tracking-by-detection的创制人,Ensemble
Tracking, SVM Tracking;

20.Visual Information Processing and
Learning
:中科院总结所,山世光先生的琢磨组,不需介绍了呢;

21.Shaogang Gong:Queen Mary
University of London,各种PAMI,IJCV;

22.Yang
Jian
:里士满农林大学,2DPCA,人脸识别;

23.CALVIN:weakly
supervised learning,objectness;

24.Learning & Vision Group:NUS,稀疏代表;

26.Xiaogang Wang:CUHK,active &
fruitful,行人检测,群体行为分析;

27.Zhou,
Bolei
:下边Wang老师硕士大学生,群体行为,看看人家的Publications已经轻松甩国内博士好几条街;

28.Computational Vision
Group
:Leader–Deva
Ramanan

29.Zhang
Lei
:加州伯克利分校州立,稀疏表示,人脸识别,可以算大中华区相比活跃的探讨组了,几乎每篇杂谈都有对应源码

30.Zhang
Kaihua
:下面Zhang老师学生,Compressive
Tracking

31.Pramod
Sharma
:离线磨练检测器的在线自适应,貌似是个不错的topic;

32.Loris Bazzani:person
re-id,他的SDALF(code)描述子平常被用来做为相比较对象,表达或者有参考价值的;

33.Pedro
Felzenszwalb
:布朗(布朗)大学,目的检测,新新N人一枚;

34.Vijayakumar
Bhagavatula
:IEEE Fellow, correlation filters;

35.Laurens van der
Maaten
:MLer.

 

 

 

牛人主页(主页有这个杂文代码)

Serge Belongie at UC San Diego

Antonio Torralba at MIT

Alexei Ffros at CMU

Ce Liu at Microsoft Research New
England

Vittorio Ferrari at
Univ.of Edinburgh

Kristen Grauman at UT Austin

Devi
Parikh
 at  TTI-Chicago (Marr
Prize at ICCV2011)

John Wright at Columbia Univ.

Piotr Dollar at CalTech

Boris Babenko at UC San Diego

David Ross at Google/Youtube

David Donoho at
Stanford Univ.

 

 

大神们:

 

William T. Freeman at MIT

Roberto Cipolla at
Cambridge

David Lowe at Univ. of British Columbia

Mubarak Shah at
Univ. of Central Florida

Yi Ma at MSRA

Tinne Tuytelaars at K.U.
Leuven

Trevor Darrell at U.C. Berkeley

Michael J. Black at Brown Univ.

 

 

 

 

着重探究组:

 

Computer Vision
Group
 at UC
Berkeley

Robotics Research Group at Univ. of
Oxford

LEAR at INRIA

Computer Vision Lab at Stanford

Computer Vision Lab at EPFL

Computer Vision Lab at ETH Zurich

Computer Vision Lab at Seoul National Univ.

Computer Vision Lab at UC San Diego

Computer Vision Lab at UC Santa Cruz

Computer Vision Lab at
Univ. of Southern California

Computer Vision Lab at Univ. of
Central Florida

Computer Vision Lab at Columbia
Univ.

UCLA Vision Lab

Motion and Shape Computing Group at
George Mason Univ.

Robust Image Understanding Lab at
Rutgers Univ.

Intelligent Vision Systems
Group
 at Univ. of Bonn

Institute for Computer Graphics and
Vision
 at Graz Univ. of Tech.

Computer Vision Lab. at Vienna Univ.
of Tech. 

Computational Image Analysis and
Radiology
 at Medical Univ. of Vienna

Personal Robotics Lab at
CMU

Visual Perception Lab at
Purdue Univ.

 

 

潜力牛人:

 

Juergen Gall at ETH Zurich

Matt Flagg at Georgia Tech.

Mathieu Salzmann at TTI-Chicago

Gerg Shakhnarovich at TTI-Chicago

Taeg Sang Cho at MIT

Jianchao Yang at UIUC

Stefan Roth at TU
Darmstadt

Peter
Kontschieder
 at
Graz Univ. of Tech.

Dominik Alexander Klein at Univ.
of Bonn

Yinan Yu at CASIA (PASCAL VOC
2010 Detection Challenge Winner)

Zdenek Kalal at FPFL

Julien Pilet at FPFL

Kenji Okuma

 

2 私房、探究机关链接

(1)googleResearch; http://research.google.com/index.html
(2)MIT硕士,汤晓欧学生林达华;http://people.csail.mit.edu/dhlin/index.html
(3)MIT博士后Douglas Lanman; http://web.media.mit.edu/~dlanman/
(4)opencv中文网站;http://www.opencv.org.cn/index.php/%E9%A6%96%E9%A1%B5
(5)Stanford大学vision实验室; http://vision.stanford.edu/research.html
(6)Stanford高校大学生崔靖宇; http://www.stanford.edu/~jycui/
(7)UCLA讲师朱松纯; http://www.stat.ucla.edu/~sczhu/
(8)中国人造智能网; http://www.chinaai.org/
(9)中国视觉网; http://www.china-vision.net/
(10)中科院自动化所; http://www.ia.cas.cn/
(11)中科院自动化所李子青探讨员; http://www.cbsr.ia.ac.cn/users/szli/
(12)中科院总结所山世光研究员; http://www.jdl.ac.cn/user/sgshan/
(13)人脸识别主页; http://www.face-rec.org/
(14)加州高校伯克利(Berkeley)(Berkeley)分校CV小组;http://www.eecs.berkeley.edu/Research/Projects/CS/vision/

(15)南加州大学CV实验室; http://iris.usc.edu/USC-Computer-Vision.html
(16)卡内基(Carnegie)梅隆高校CV主页;

http://www.cs.cmu.edu/afs/cs/project/cil/ftp/html/vision.html

(17)微软CV研究员Richard
Szeliski;http://research.microsoft.com/en-us/um/people/szeliski/
(18)微软欧洲探究院总计机视觉探究组; http://research.microsoft.com/en-us/groups/vc/
(19)微软香港理工探究院ML与CV商讨组; http://research.microsoft.com/en-us/groups/mlp/default.aspx

(20)研学论坛; http://bbs.matwav.com/
(21)弥利坚Rutgers大学助理讲师刘青山;http://www.research.rutgers.edu/~qsliu/
(22)统计机视觉最新资讯网; http://www.cvchina.info/
(23)运动检测、阴影、跟踪的测试视频下载;http://apps.hi.baidu.com/share/detail/18903287
(24)香港中文大学助理助教王晓刚; http://www.ee.cuhk.edu.hk/~xgwang/
(25)香岛中文大学多媒体实验室(汤晓鸥); http://mmlab.ie.cuhk.edu.hk/
(26)U.C. San Diego. computer
vision;http://vision.ucsd.edu/content/home
(27)CVonline; http://homepages.inf.ed.ac.uk/rbf/CVonline/
(28)computer vision
software; http://peipa.essex.ac.uk/info/software.html
(29)Computer Vision Resource; http://www.cvpapers.com/
(30)computer vision research
groups;http://peipa.essex.ac.uk/info/groups.html
(31)computer vision center; http://computervisioncentral.com/cvcnews

(32)海南高校图像技术探讨与应用(ITRA)团队:http://www.dvzju.com/

(33)自动识别网:http://www.autoid-china.com.cn/

(34)南开高校章毓晋助教:http://www.tsinghua.edu.cn/publish/ee/4157/2010/20101217173552339241557/20101217173552339241557_.html

(35)一级民用机器人探究小组Porf.加里领导的威尔ow
Garage:http://www.willowgarage.com/

(36)日本首都矿业大学图像处理与形式识别商讨所:http://www.pami.sjtu.edu.cn/

(37)香港中医药大学总计机视觉实验室刘允才讲师:http://www.visionlab.sjtu.edu.cn/

(38)内华葫芦岛高校奥斯汀(Austen)分校助理教师Kristen Grauman
http://www.cs.utexas.edu/~grauman/ 图像分解,检索

(39)复旦高校电子工程系智能图文音信处理实验室(丁晓青讲师):http://ocrserv.ee.tsinghua.edu.cn/auto/index.asp

(40)香港高校高文教师:http://www.jdl.ac.cn/htm-gaowen/

(41)厦大高校艾海舟讲师:http://media.cs.tsinghua.edu.cn/cn/aihz

(42)中科院生物识别与安全技术研讨主题:http://www.cbsr.ia.ac.cn/china/index%20CH.asp

(43)瑞士联邦伯明翰大学 托马斯(Thomas)(Thomas)Vetter教书:http://informatik.unibas.ch/personen/vetter_t.html

(44)西弗吉尼亚州立大学 RobHess硕士:http://blogs.oregonstate.edu/hess/

(45)布里斯(Rhys)班大学 于仕祺副教师:http://yushiqi.cn/

(46)布Rhys托(Stowe)政法大学人工智能与机器人探讨所:http://www.aiar.xjtu.edu.cn/

(47)Carnegie梅隆大学探究员罗伯特(Robert)(Bert) T.
Collins:http://www.cs.cmu.edu/~rcollins/home.html#Background

(48)MIT博士Chris
Stauffer:http://people.csail.mit.edu/stauffer/Home/index.php

(49)美利坚联邦合众国内华达州立研究生物识别研讨组(Anil K.
Jain助教):http://www.cse.msu.edu/rgroups/biometrics/

(50)美利哥印第安纳州立大学托马斯(Thomas)(Thomas) S.
Huang:http://www.beckman.illinois.edu/directory/t-huang1

(51)罗利大学数字水墨画测量与总括机视觉研商为主:http://www.whudpcv.cn/index.asp

(52)瑞士联邦澳门大学山姆i
Romdhani助理研商员:http://informatik.unibas.ch/personen/romdhani_sami/

(53)CMU大学研究员Yang Wang:http://www.cs.cmu.edu/~wangy/home.html

(54)英帝国加尔各答高校提姆(Tim)Cootes助教:http://personalpages.manchester.ac.uk/staff/timothy.f.cootes/

(55)美利坚同盟国罗彻斯特大学助教Jiebo Luo:http://www.cs.rochester.edu/u/jluo/

(56)U.S.普渡高校机器人视觉实验室:https://engineering.purdue.edu/RVL/Welcome.html

(57)美利坚合众国Audi州立高校感知、运动与认识实验室:http://vision.cse.psu.edu/home/home.shtml

(58)米国牛津高校GRASP实验室:https://www.grasp.upenn.edu/

(59)美利坚同盟国内达华大学里诺校区CV实验室:http://www.cse.unr.edu/CVL/index.php

(60)美利哥密西根大学vision实验室:http://www.eecs.umich.edu/vision/index.html

(61)University of
Massachusetts(麻省大学),视觉实验室:http://vis-www.cs.umass.edu/index.html

(62)华盛顿(华盛顿)大学大学生后Iva
Kemelmacher:http://www.cs.washington.edu/homes/kemelmi

(63)以色列魏茨曼农林大学Ronen
Basri:http://www.wisdom.weizmann.ac.il/~ronen/index.html

(64)瑞士ETH-Zurich大学CV实验室:http://www.vision.ee.ethz.ch/boostingTrackers/index.htm

(65)微软CV研讨员张正友:http://research.microsoft.com/en-us/um/people/zhang/

(66)中科院自动化所法学映像研讨室:http://www.3dmed.net/

(67)中科院田捷探讨员:http://www.3dmed.net/tian/

(68)微软Redmond商量院钻探员SimonBaker:http://research.microsoft.com/en-us/people/sbaker/

(69)普林斯顿大学讲授李凯:http://www.cs.princeton.edu/~li/
(70)普林斯顿大学学士贾登:http://www.cs.princeton.edu/~jiadeng/
(71)伊利诺伊香槟分校高校教学安德鲁 Zisserman: http://www.robots.ox.ac.uk/~az/
(72)大英帝国leeds大学琢磨员Mark伊夫(Eve)ringham:http://www.comp.leeds.ac.uk/me/
(73)大英帝国圣路易斯高校教书Chris威尔iam: http://homepages.inf.ed.ac.uk/ckiw/
(74)微软哈佛研究院研商员约翰(John) Winn: http://johnwinn.org/
(75)路易斯安那交通大学助教Monson
H.Hayes:http://savannah.gatech.edu/people/mhayes/index.html
(76)微软亚洲商讨院研究员孙剑:http://research.microsoft.com/en-us/people/jiansun/
(77)微软南美洲商讨院探讨员马毅:http://research.microsoft.com/en-us/people/mayi/
(78)大英帝国哥伦比亚高校教书大卫 Lowe: http://www.cs.ubc.ca/~lowe/
(79)大不列颠及北爱尔兰联合王国明尼阿波莉(波莉(Polly))斯高校教学鲍勃 Fisher: http://homepages.inf.ed.ac.uk/rbf/
(80)加州大学旧金山分校讲师Serge
J.Belongie:http://cseweb.ucsd.edu/~sjb/
(81)南卡罗来纳大学教学Charles R.Dyer: http://pages.cs.wisc.edu/~dyer/
(82)法兰克福大学讲师Allan.Jepson: http://www.cs.toronto.edu/~jepson/
(83)伦斯勒医科大学讲师Qiang Ji: http://www.ecse.rpi.edu/~qji/
(84)CMU研究员Daniel
Huber: http://www.ri.cmu.edu/person.html?person_id=123
(85)布鲁塞尔大学教学:大卫(David) J.Fleet: http://www.cs.toronto.edu/~fleet/
(86)London高校Mary女王高校讲师AndreaCavallaro:http://www.eecs.qmul.ac.uk/~andrea/
(87)阿姆斯特丹大学教书Kyros Kutulakos: http://www.cs.toronto.edu/~kyros/
(88)杜克(杜克)大学讲授Carlo Tomasi: http://www.cs.duke.edu/~tomasi/
(89)CMU教授Martial Hebert: http://www.cs.cmu.edu/~hebert/
(90)MIT助理教师Antonio Torralba: http://web.mit.edu/torralba/www/
(91)伊利诺伊大学探究员Yasel
Yacoob: http://www.umiacs.umd.edu/users/yaser/
(92)康奈尔大学教师Ramin Zabih: http://www.cs.cornell.edu/~rdz/

(93)CMU研究生田渊栋: http://www.cs.cmu.edu/~yuandong/
(94)CMU副教授Srinivasa Narasimhan: http://www.cs.cmu.edu/~srinivas/
(95)CMU大学ILIM实验室:http://www.cs.cmu.edu/~ILIM/
(96)哥伦比亚高校讲授Sheer K.Nayar: http://www.cs.columbia.edu/~nayar/
(97)MITSUBISHI电子研讨院研商员Fatih Porikli :http://www.porikli.com/
(98)康奈尔大学教学Daniel Huttenlocher:http://www.cs.cornell.edu/~dph/
(99)南京大学讲授周志华:http://cs.nju.edu.cn/zhouzh/index.htm
(100)阿姆斯特丹丰田技术探讨所助理助教Devi Parikh:
http://ttic.uchicago.edu/~dparikh/index.html
(101)瑞士体育高校研究生后Helmut
Grabner:http://www.vision.ee.ethz.ch/~hegrabne/#Short_CV

(102)香岛普通话大学讲师贾佳亚:http://www.cse.cuhk.edu.hk/~leojia/index.html

(103)利伯维尔高校教学吴建鑫:http://c2inet.sce.ntu.edu.sg/Jianxin/index.html

(104)GE探究院研商员李关:http://www.cs.unc.edu/~lguan/

(105)内华达财经政法大学教书Monson
Hayes:http://savannah.gatech.edu/people/mhayes/

(106)图片检索国际竞技PASCAL
VOC(微软华盛顿圣路易斯分校研究院社团):http://pascallin.ecs.soton.ac.uk/challenges/VOC/

(107)机器视觉开源处理库汇总:http://archive.cnblogs.com/a/2217609/

(108)布朗(Brown)大学讲师本杰明(Benjamin) Kimia: http://www.lems.brown.edu/kimia.html 

(109)数据堂-图像处理有关的样本数量:http://www.datatang.com/data/list/602026/p1

(110)东软基于CV的汽车帮助驾驶系统:http://www.neusoft.com/cn/solutions/1047/

(111)印第安纳高校教学Rema Chellappa:http://www.cfar.umd.edu/~rama/

(112)阿姆斯特丹丰田研讨中央助理员助教Devi
Parikh:http://ttic.uchicago.edu/~dparikh/index.html

(113)内华达州立高校助理员教师石建波:http://www.cis.upenn.edu/~jshi/

(114)比利(比尔(Bill)y)时鲁汶大学教师Luc Van
Gool:http://www.vision.ee.ethz.ch/members/get_member.cgi?id=1http://www.vision.ee.ethz.ch/~vangool/

(115)行人检测主页:http://www.pedestrian-detection.com/

(116)法兰西学习算法与系统实验室Basilio
Noris学士:http://lasa.epfl.ch/people/member.php?SCIPER=129576 http://mldemos.epfl.ch/

(117)U.S.A.加利福尼亚大学LARRY S.DAVIS助教:http://www.umiacs.umd.edu/~lsd/

(118)总计机视觉杂文分类导航:http://www.visionbib.com/bibliography/contents.html

(119)总结机视觉分类音信导航:http://www.visionbib.com/

(120)西班牙孟买体育大学大学生Marcos Nieto:http://marcosnieto.net/

(121)帝国师范高校副教师张磊:http://www4.comp.polyu.edu.hk/~cslzhang/

(122)以色列技术大学教书MichaelElad:http://www.cs.technion.ac.il/~elad/

(123)南朝鲜启明大学总括机视觉与形式识别实验室:http://cvpr.kmu.ac.kr/

(124)英帝国诺丁汉高校Michel Valstar硕士:http://www.cs.nott.ac.uk/~mfv/

(125)卡内基梅隆高校Takeo
Kanade讲师:http://www.ri.cmu.edu/people/kanade_takeo.html

(126)微软学术搜索:http://libra.msra.cn/

(127)比利(比尔(Bill)y)时天主教鲁汶大学Radu
提姆(Tim)ofte硕士:http://homes.esat.kuleuven.be/~rtimofte/,交通标志检测,定位,3D跟踪

(128)迪斯尼长沙研商院研讨员:Iain
马修s:http://www.iainm.com/iainm/Home.html

http://www.ri.cmu.edu/person.html?type=publications&person_id=741 AAM,三维重建

(129)康奈尔大学视觉与图像分析组:http://www.via.cornell.edu/
农学图像处理

(130)密西根州立研究生物识别探讨组:http://www.cse.msu.edu/biometrics/
人脸识别、指纹识别、图像检索
(131)柏林(Berlin)医科大学统计机视觉与遥感实验室:http://www.cv.tu-berlin.de/menue/computer\_vision\_remote\_sensing/parameter/en/
图像分析、物体重建、基于图像的表面测量、艺术学图像处理

(132)大英帝国马尔默高校数字多媒体探讨组:http://www.cs.bris.ac.uk/Research/Digitalmedia/
运动检测与跟踪、视频压缩、3D重建、字符定位

(133)英国萨利(Surrey)大学视觉、语音与信号处理为主:
http://www.surrey.ac.uk/cvssp/   人脸识别、监控、3D、视频查找、
(134)北卡莱罗纳大学教堂山分校Marc
Pollefeys教师:http://www.cs.unc.edu/~marc/
基于录像的3D模型生成、相机标定、运动检测与分析、3D重建

(135)威斯康星麦迪逊分校高校Richard哈特(Hart)ley讲师:http://users.cecs.anu.edu.au/~hartley/
运动揣测、稀疏子空间、跟踪、

(136)百度技能副老总于凯:http://www.dbs.ifi.lmu.de/~yu\_k/
深度学习,稀疏代表,图像分类

(137)苏州电子交通大学高新波讲师:http://web.xidian.edu.cn/xbgao/index.html 质料评议、水印、稀疏表示、超分辨率

(138)加州高校伯克利(Berkeley)分校MichaelI.乔丹(Jordan)助教:http://www.cs.berkeley.edu/~jordan/ 机器学习

(139)牛津行人检测相关材料:http://www.vision.caltech.edu/Image\_Datasets/CaltechPedestrians/

(140)微软Redmond啄磨院商量员Piotr
Dollar: http://vision.ucsd.edu/~pdollar/ 行人检测、特征提取、

(141)视觉总括探究论坛:http://www.sigvc.org/bbs/
中科院视觉总结琢磨小组的论坛

(142)美利坚合众国坦桑尼亚州立大学稀疏学习软件包:http://www.public.asu.edu/~jye02/Software/SLEP/index.htm
稀疏学习

(143)美利坚联邦合众国加州大学圣菲波哥大分校雅各布(Jacob)Whitehill研究生:http://mplab.ucsd.edu/~jake/ 机器学习

(144)美利坚联邦合众国布朗(Brown)大学迈克尔(Michael)(Michael) J.布莱克教师:http://cs.brown.edu/~black/
 人的态度猜想和跟踪

(145)美利坚联邦合众国加州高校圣菲波哥大分校大卫(David)Kriegman教师:http://cseweb.ucsd.edu/~kriegman/ 人脸识别

(146)南加州大学保罗 Debevec教师:http://ict.debevec.org/~debevec/
或 http://www.pauldebevec.com/ 将CV和CG结合研商 人脸捕捉重建技术

(147)北达科他高校D.A.Forsyth助教:http://luthuli.cs.uiuc.edu/~daf/
三维重建

(148)大英帝国宾夕法尼亚州立大学伊恩(Ian)Reid教授:http://www.robots.ox.ac.uk/~ian/ 跟踪和机器人导航

(149)CMU大学Alyosha Efros 教授: https://www.cs.cmu.edu/~efros/
图像纹理合成

(150)加州高校伯克利(Berkeley)(Berkeley)分校Jitendra
Malik助教:http://www.cs.berkeley.edu/~malik/ 轮廓检测、图像/视频分割、图形匹配、目标识别

(151)MIT教授William Freeman: http://people.csail.mit.edu/billf/
图像纹理合成

(152)CMU博士Henry
Schneiderman: http://www.cs.cmu.edu/~hws/ 目的检测和甄别;

(153)微软研讨员PaulViola: http://research.microsoft.com/en-us/um/people/viola/ AdaBoost算法

(154)微软商量员Antonio
Criminisi: http://research.microsoft.com/en-us/people/antcrim/
图像修补,三维重建,指标检测与跟踪;

(155)魏茨曼科学探讨所助教Michal
Irani: http://www.wisdom.weizmann.ac.il/~irani/ 超分辨率

(156)瑞士联邦大连传媒大学Pascal
Fua讲师:http://people.epfl.ch/pascal.fua/bio?lang=en 立体视觉,增强现实

(157)西弗吉尼亚农业大学Irfan
Essa助教:http://www.ic.gatech.edu/people/irfan-essa 人脸表情识别

(158)中科院助理教师樊彬:http://www.sigvc.org/bfan/ 特征描述;

(159)新加坡国立大学Sebastian
Thrun教师:http://robots.stanford.edu/index.html 机器人;

(160)法兰克福高校杰弗里E.Hinton讲师:http://www.cs.toronto.edu/~hinton/ 深度学习

(161)凤巢系统架构师张栋硕士:http://weibo.com/machinelearning

(162)二零一二年龙星计划机器学习课程:http://bigeye.au.tsinghua.edu.cn/DragonStar2012/index.html

(163)中科院自动化所肖柏华教师:http://www.compsys.ia.ac.cn/people/xiaobaihua.html 文字识别、人脸识别、质料评议

(164)图像录像质料鉴定:http://live.ece.utexas.edu/research/quality/

(165)伦敦高校Yann LeCun教师http://yann.lecun.com/ 
 http://yann.lecun.com/exdb/mnist/  手写体数字识别

(166)二维条码识别开源库zxing:http://code.google.com/p/zxing/

(167)布朗(Brown)高校Pedro
Felzenszwalb助教:http://cs.brown.edu/~pff/ 特征提取,Deformable Part
Model

(168)新罕布什尔香槟大学Svetlana
Lazebnik助教:http://www.cs.illinois.edu/homes/slazebni/ 特征提取,聚类,图像检索

(169)荷兰王国乌德勒支高校图像与多媒体探究中央http://www.cs.uu.nl/centers/give/multimedia/index.html 图像、多媒体检索与配合

(170)英国格拉斯哥学院信息寻找小组:http://ir.dcs.gla.ac.uk/ 文本、图像、视频查找

(171)中科院自动化所孙哲南助手教师:http://www.cbsr.ia.ac.cn/users/znsun/ 虹膜识别、掌纹识别、人脸识别

(172)科伦坡信息工程高校刘青山助教:http://www.jstuoke.com/web/xky/detail.asp?NewsID=1096 人脸图像分析、管医学图像分析

(173)武大高校助理员助教冯建江:http://ivg.au.tsinghua.edu.cn/~jfeng/ 指纹识别

(174)北航助理助教黄迪:http://irip.buaa.edu.cn/~dihuang/ 3D人脸识别

(175)嘉兴大学助理员讲师郑伟诗:http://sist.sysu.edu.cn/~zhwshi/ 人脸识别、特征匹配、聚类、检索;

(176)google瑞士联邦维也纳的工程师托马斯(Thomas)(Thomas)Deselaers: http://thomas.deselaers.de/index.html 图像检索

(177)百度深度学习钻探为主大学生后余轶南:http://www.cbsr.ia.ac.cn/users/ynyu/index.htm 目的检测,图像检索

(178)威兹曼理工大学超分辨率:http://www.wisdom.weizmann.ac.il/~vision/SingleImageSR.html

(179)马里兰高校Austen分校Al
Bovik讲师:http://live.ece.utexas.edu/people/bovik/ 图像摄像质地判别、特征提取

(180)以色列希伯来大学Yair
Weiss助教:http://www.cs.huji.ac.il/~yweiss/ 机器学习、超分辨率

(181)以色列希伯来大学Daniel
卓拉(Zora)n学士:http://www.cs.huji.ac.il/~daniez/ 超分辨率、去噪

(182)弥利坚加州高校Peyman
Milanfar讲师:http://users.soe.ucsc.edu/~milanfar/ 去噪

(183)中科院总计所副研究员常虹:http://www.jdl.ac.cn/user/hchang/index.html 图像检索、半督察学习、超分辨率

(184)以色列威茨曼高校Anat
Levin讲师:http://www.wisdom.weizmann.ac.il/~levina/ 去噪、去模糊

(185)以色列威茨曼大学Daniel
Glasner学士后:http://www.wisdom.weizmann.ac.il/~glasner/ 超分辨率、分割、姿态估算

(186)密西根高校助理讲师Honglak
Lee: http://web.eecs.umich.edu/~honglak/ 机器学习、特征提取,去噪、稀疏代表;

(187)MIT周博磊硕士:http://people.csail.mit.edu/bzhou/ 聚集分析、运动检测

(188)米利坚南达科他大学Li
He研究生:http://web.eecs.utk.edu/~lhe4/ 稀疏代表、超分辨率;

(189)Adobe研究院Jianchao
Yang研究员:http://www.ifp.illinois.edu/~jyang29/ 稀疏表示,超分辨率、图片检索、去噪、去模糊

(190)Deep
Learning主页:http://deeplearning.net/ 深度学习论文、软件,代码,demo,数据等;

(191)洛桑联邦理工高校安德鲁Ng助教:http://cs.stanford.edu/people/ang/ 深度神经网络,深度学习

(192)Elefant: http://elefant.developer.nicta.com.au/ 机器学习开源库

(193)微软研讨员Ce
Liu: http://people.csail.mit.edu/celiu/ 去噪、超分辨率、去模糊、分割

(194)韦斯特(West) 维吉妮亚(Virginia)高校助理员助教Xin
Li: http://www.csee.wvu.edu/~xinl/ 边缘检测、降噪、去模糊

(195)http://www.csee.wvu.edu/~xinl/source.html 深度学习、去噪、编码、压缩感知、超分辨率、聚类、分割等有关代码集合

(196)西班牙格拉纳达高校超分辨率重建项目组:http://decsai.ugr.es/pi/superresolution/index.html

(197)哈工大大学程明明硕士:http://mmcheng.net/ 图像分割、检索

(198)香港理工布鲁克(Brooke)斯大学PhilipH.S.Torr讲师:http://cms.brookes.ac.uk/staff/PhilipTorr/ 分割、三维重建

(199)宾夕法尼亚医科大学詹姆士M.Rehg教师:http://www.cc.gatech.edu/~rehg/ 分割、行人检测、特征描述、

(200)大规模图像分类、检测竞技ILSVRC(Stanford, Google举行):

 http://www.image-net.org/challenges/LSVRC/2013/

(201)加州大学尔湾分校Deva
Ramanan助理教师:http://www.ics.uci.edu/~dramanan/ 目的检测,行人检测,跟踪、稀疏代表

(202)人脸识别测试图片集:http://www.mlcv.net/

(203)美利哥西哈工大学学士Ming
Yang: http://www.ece.northwestern.edu/~mya671/ 人脸识别、图像检索;

(204)美利坚同盟国加州大学Berkeley分校学士后Ross
B.Girshick:http://www.cs.berkeley.edu/~rbg/ 目的检测(DPM)

(205)粤语语言资源联盟:http://www.chineseldc.org/index.html
 内有广大语言识别、字符识其它磨炼,测试库;

(206)西班牙巴塞罗这大学统计机视觉核心:http://www.cvc.uab.es/adas/site/
检测、跟踪、3D、行人检测、汽车襄助驾驶

(207)德意志联邦共和国DAIMLER探究所Prof. Dr. Dariu M.
Gavrila:http://www.gavrila.net/index.html 跟踪、行人检测、

(208)特拉维夫联邦交通高校安德莉亚(Andrea)s
Ess硕士后:http://www.vision.ee.ethz.ch/~aess/ 行人检测、行为检测、跟踪

(209)Libqrencode: http://fukuchi.org/works/qrencode/
基于C语言的QR二维码编码开源库

(210)海南农林科技大学袁飞牛讲师:http://sit.jxufe.cn/grbk/yfn/index.html\#
 烟雾检测、3D重建、农学图像处理

(211)火奴鲁鲁高校Raanan Fattal助教:http://www.cs.huji.ac.il/~raananf/
 图像增强、

(212)布尔萨大学Dani Lischnski教师:http://www.cs.huji.ac.il/~danix/
去模糊、纹理合成、图像增强

3 代码汇总

 

一、特征提取Feature Extraction:

二、图像分割Image Segmentation:

三、目的检测Object Detection:

四、显明性检测Saliency Detection:

五、图像分类、聚类Image Classification, Clustering

六、抠图Image Matting

七、目标跟踪Object Tracking:

八、Kinect:

九、3D相关:

十、机器学习算法:

十一、目标、行为识别Object, Action Recognition:

十二、图像处理:

十三、一些实用工具:

十四、人手及手指检测与识别:

十五、场景解释:

十六、光流Optical flow:

十七、图像检索Image Retrieval:

十八、马尔科夫随机场马克(Mark)ov Random Field(Field)s:

十九、运动检测Motion detection:

Fast Keypoint Detectors for Real-time Applications:

-   [FAST](http://www.edwardrosten.com/work/fast.html) – High-speed
    corner detector implementation for a wide variety of platforms

-   [AGAST](http://www6.in.tum.de/Main/ResearchAgast) – Even faster
    than the FAST corner detector. A multi-scale version of this
    method is used for the BRISK descriptor (ECCV 2010).



Binary Descriptors for Real-Time Applications:

-   [BRIEF](http://cvlab.epfl.ch/software/brief/) – C++ code for a
    fast and accurate interest point descriptor (not invariant to
    rotations and scale) (ECCV 2010)

-   [ORB](http://docs.opencv.org/modules/features2d/doc/feature_detection_and_description.html) –
    OpenCV implementation of the Oriented-Brief (ORB) descriptor
    (invariant to rotations, but not scale)

-   [BRISK](http://www.asl.ethz.ch/people/lestefan/personal/BRISK) –
    Efficient Binary descriptor invariant to rotations and scale. It
    includes a Matlab mex interface. (ICCV 2011)

-   [FREAK](http://www.ivpe.com/freak.htm) – Faster than BRISK
    (invariant to rotations and scale) (CVPR 2012)



SIFT and SURF Implementations:

-   SIFT: [VLFeat](http://www.vlfeat.org/), [OpenCV](http://docs.opencv.org/modules/nonfree/doc/feature_detection.html), [Original
    code](http://www.cs.ubc.ca/~lowe/keypoints/) by David Lowe, [GPU
    implementation](http://cs.unc.edu/~ccwu/siftgpu/), [OpenSIFT](http://robwhess.github.com/opensift/)

-   SURF: [Herbert Bay’s
    code](http://www.vision.ee.ethz.ch/~surf/), [OpenCV](http://docs.opencv.org/modules/nonfree/doc/feature_detection.html), [GPU-SURF](http://www.visual-experiments.com/demos/gpusurf/)



Other Local Feature Detectors and Descriptors:

-   [VGG Affine Covariant
    features](http://www.robots.ox.ac.uk/~vgg/research/affine/) –
    Oxford code for various affine covariant feature detectors and
    descriptors.

-   [LIOP
    descriptor](http://vision.ia.ac.cn/Students/wzh/publication/liop/index.html) –
    Source code for the Local Intensity order Pattern (LIOP)
    descriptor (ICCV 2011).

-   [Local Symmetry
    Features](http://www.cs.cornell.edu/projects/symfeat/) – Source
    code for matching of local symmetry features under large
    variations in lighting, age, and rendering style (CVPR 2012).



Global Image Descriptors:

-   [GIST](http://people.csail.mit.edu/torralba/code/spatialenvelope/) –
    Matlab code for the GIST descriptor

-   [CENTRIST](https://sites.google.com/site/wujx2001/home) – Global
    visual descriptor for scene categorization and object detection
    (PAMI 2011)

 

Feature Coding and Pooling

-   [VGG Feature Encoding
    Toolkit](http://www.robots.ox.ac.uk/~vgg/software/enceval_toolkit/) –
    Source code for various state-of-the-art feature encoding
    methods – including Standard hard encoding, Kernel codebook
    encoding, Locality-constrained linear encoding, and Fisher
    kernel encoding.

-   [Spatial Pyramid
    Matching](http://www.cs.illinois.edu/homes/slazebni/) – Source
    code for feature pooling based on spatial pyramid matching
    (widely used for image classification)

 

Convolutional Nets and Deep Learning

-   [EBLearn](http://eblearn.sourceforge.net/) – C++ Library for
    Energy-Based Learning. It includes several demos and
    step-by-step instructions to train classifiers based on
    convolutional neural networks.

-   [Torch7](http://www.torch.ch/) – Provides a matlab-like
    environment for state-of-the-art machine learning algorithms,
    including a fast implementation of convolutional neural
    networks.

-   [Deep Learning](http://deeplearning.net/software_links/) -
    Various links for deep learning software.

 

Part-Based Models

 

-   [Deformable Part-based
    Detector](http://people.cs.uchicago.edu/~rbg/latent/) – Library
    provided by the authors of the original paper (state-of-the-art
    in PASCAL VOC detection task)

-   [Efficient Deformable Part-Based
    Detector](http://vision.mas.ecp.fr/Personnel/iasonas/dpms.html) –
    Branch-and-Bound implementation for a deformable part-based
    detector.

-   [Accelerated Deformable Part
    Model](http://www.idiap.ch/~cdubout/coding.html) – Efficient
    implementation of a method that achieves the exact same
    performance of deformable part-based detectors but with
    significant acceleration (ECCV 2012).

-   [Coarse-to-Fine Deformable Part
    Model](http://iselab.cvc.uab.es/CoarseToFine) – Fast approach
    for deformable object detection (CVPR 2011).

-   [Poselets](http://www.eecs.berkeley.edu/~lbourdev/poselets/) –
    C++ and Matlab versions for object detection based on poselets.

-   [Part-based Face Detector and Pose
    Estimation](http://www.ics.uci.edu/~xzhu/face/) – Implementation
    of a unified approach for face detection, pose estimation, and
    landmark localization (CVPR 2012).

     

    Attributes and Semantic Features

    -   [Relative
        Attributes](http://ttic.uchicago.edu/~dparikh/relative.html#code) –
        Modified implementation of RankSVM to train Relative
        Attributes (ICCV 2011).

    -   [Object
        Bank](http://vision.stanford.edu/projects/objectbank/) –
        Implementation of object bank semantic features (NIPS 2010).
        See
        also [ActionBank](http://www.cse.buffalo.edu/~jcorso/r/actionbank/)

    -   [Classemes, Picodes, and Meta-class
        features](http://vlg.cs.dartmouth.edu/projects/vlg_extractor/vlg_extractor/Home.html) –
        Software for extracting high-level image descriptors (ECCV
        2010, NIPS 2011, CVPR 2012).

    Large-Scale Learning

    -   [Additive
        Kernels](http://ttic.uchicago.edu/~smaji/projects/fiksvm/) –
        Source code for fast additive kernel SVM classifiers (PAMI
        2013).

    -   [LIBLINEAR](http://www.csie.ntu.edu.tw/~cjlin/liblinear/) –
        Library for large-scale linear SVM classification.

    -   [VLFeat](http://www.vlfeat.org/) – Implementation for
        Pegasos SVM and Homogeneous Kernel map.

    Fast Indexing and Image Retrieval

    -   [FLANN](http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN) –
        Library for performing fast approximate nearest neighbor.

    -   [Kernelized
        LSH](http://www.cse.ohio-state.edu/~kulis/klsh/klsh.htm) –
        Source code for Kernelized Locality-Sensitive Hashing (ICCV
        2009).

    -   [ITQ Binary codes](http://www.unc.edu/~yunchao/itq.htm) –
        Code for generation of small binary codes using Iterative
        Quantization and other baselines such as
        Locality-Sensitive-Hashing (CVPR 2011).

    -   [INRIA Image
        Retrieval](http://lear.inrialpes.fr/src/inria_fisher/) –
        Efficient code for state-of-the-art large-scale image
        retrieval (CVPR 2011).

    Object Detection

    -   See [Part-based
        Models](http://rogerioferis.com/VisualRecognitionAndSearch/Resources.html#parts) and [Convolutional
        Nets](http://rogerioferis.com/VisualRecognitionAndSearch/Resources.html#convnets) above.

    -   [Pedestrian Detection at
        100fps](https://bitbucket.org/rodrigob/doppia) – Very fast
        and accurate pedestrian detector (CVPR 2012).

    -   [Caltech Pedestrian Detection
        Benchmark](http://www.vision.caltech.edu/Image_Datasets/CaltechPedestrians/) –
        Excellent resource for pedestrian detection, with various
        links for state-of-the-art implementations.

    -   [OpenCV](http://docs.opencv.org/trunk/modules/objdetect/doc/cascade_classification.html?highlight=face%20detection) –
        Enhanced implementation of Viola&Jones real-time object
        detector, with trained models for face detection.

    -   [Efficient Subwindow
        Search](https://sites.google.com/site/christophlampert/software) –
        Source code for branch-and-bound optimization for efficient
        object localization (CVPR 2008).

    3D Recognition

    -   [Point-Cloud Library](http://www.pointclouds.org/) – Library
        for 3D image and point cloud processing.

    Action Recognition

    -   [ActionBank](http://www.cse.buffalo.edu/~jcorso/r/actionbank/) –
        Source code for action recognition based on the ActionBank
        representation (CVPR 2012).

    -   [STIP
        Features](http://www.di.ens.fr/~laptev/download.html) –
        software for computing space-time interest point descriptors

    -   [Independent Subspace
        Analysis](http://ai.stanford.edu/~quocle/) – Look for
        Stacked ISA for Videos (CVPR 2011)

    -   [Velocity Histories of Tracked
        Keypoints](http://www.cs.rochester.edu/~rmessing/uradl/) -
        C++ code for activity recognition using the velocity
        histories of tracked keypoints (ICCV 2009)

    ------------------------------------------------------------------------

    Datasets

    Attributes

    -   [Animals with
        Attributes](http://attributes.kyb.tuebingen.mpg.de/) –
        30,475 images of 50 animals classes with 6 pre-extracted
        feature representations for each image.

    -   [aYahoo and
        aPascal](http://vision.cs.uiuc.edu/attributes/) – Attribute
        annotations for images collected from Yahoo and Pascal
        VOC 2008.

    -   [FaceTracer](http://www.cs.columbia.edu/CAVE/databases/facetracer/) –
        15,000 faces annotated with 10 attributes and fiducial
        points.

    -   [PubFig](http://www.cs.columbia.edu/CAVE/databases/pubfig/) –
        58,797 face images of 200 people with 73 attribute
        classifier outputs.

    -   \[url=http://vis-[www.cs.umass.edu/lfw/](http://www.cs.umass.edu/lfw/)\]LFW\[/url\] –
        13,233 face images of 5,749 people with 73 attribute
        classifier outputs.

    -   [Human
        Attributes](http://www.eecs.berkeley.edu/~lbourdev/poselets/) –
        8,000 people with annotated attributes. Check also
        this [link](https://sharma.users.greyc.fr/hatdb/) for
        another dataset of human attributes.

    -   [SUN Attribute
        Database](http://cs.brown.edu/~gen/sunattributes.html) –
        Large-scale scene attribute database with a taxonomy of 102
        attributes.

    -   [ImageNet
        Attributes](http://www.image-net.org/download-attributes) –
        Variety of attribute labels for the ImageNet dataset.

    -   [Relative
        attributes](http://ttic.uchicago.edu/~dparikh/relative.html#data) –
        Data for OSR and a subset of PubFig datasets. Check also
        this [link](http://vision.cs.utexas.edu/whittlesearch/) for
        the WhittleSearch data.

    -   [Attribute Discovery
        Dataset](http://tamaraberg.com/attributesDataset/index.html) –
        Images of shopping categories associated with textual
        descriptions.

    Fine-grained Visual Categorization

    -   [Caltech-UCSD Birds
        Dataset](http://www.vision.caltech.edu/visipedia/CUB-200-2011.html) –
        Hundreds of bird categories with annotated parts and
        attributes.

    -   [Stanford Dogs
        Dataset](http://vision.stanford.edu/aditya86/ImageNetDogs/) –
        20,000 images of 120 breeds of dogs from around the world.

    -   [Oxford-IIIT Pet
        Dataset](http://www.robots.ox.ac.uk/~vgg/data/pets/) – 37
        category pet dataset with roughly 200 images for each class.
        Pixel level trimap segmentation is included.

    -   [Leeds Butterfly
        Dataset](http://www.comp.leeds.ac.uk/scs6jwks/dataset/leedsbutterfly/) –
        832 images of 10 species of butterflies.

    -   [Oxford Flower
        Dataset](http://www.robots.ox.ac.uk/~vgg/data/flowers/) –
        Hundreds of flower categories.

    Face Detection

    -   \[url=http://vis-[www.cs.umass.edu/fddb/](http://www.cs.umass.edu/fddb/)\]FDDB\[/url\] –
        UMass face detection dataset and benchmark (5,000+ faces)

    -   [CMU/MIT](http://vasc.ri.cmu.edu/idb/html/face/frontal_images/index.html) –
        Classical face detection dataset.

    Face Recognition

    -   [Face Recognition
        Homepage](http://www.face-rec.org/databases/) – Large
        collection of face recognition datasets.

    -   \[url=http://vis-[www.cs.umass.edu/lfw/](http://www.cs.umass.edu/lfw/)\]LFW\[/url\] –
        UMass unconstrained face recognition dataset (13,000+ face
        images).

    -   [NIST Face
        Homepage](http://www.nist.gov/itl/iad/ig/face.cfm) –
        includes face recognition grand challenge (FRGC), vendor
        tests (FRVT) and others.

    -   [CMU Multi-PIE](http://www.multipie.org/) – contains more
        than 750,000 images of 337 people, with 15 different views
        and 19 lighting conditions.

    -   [FERET](http://www.nist.gov/itl/iad/ig/colorferet.cfm) –
        Classical face recognition dataset.

    -   [Deng Cai’s face dataset in Matlab
        Format](http://www.cad.zju.edu.cn/home/dengcai/Data/FaceData.html) –
        Easy to use if you want play with simple face datasets
        including Yale, ORL, PIE, and Extended Yale B.

    -   [SCFace](http://www.scface.org/) – Low-resolution face
        dataset captured from surveillance cameras.

    Handwritten Digits

    -   [MNIST](http://yann.lecun.com/exdb/mnist/) – large dataset
        containing a training set of 60,000 examples, and a test set
        of 10,000 examples.

    Pedestrian Detection

    -   [Caltech Pedestrian Detection
        Benchmark](http://www.vision.caltech.edu/Image_Datasets/CaltechPedestrians/) –
        10 hours of video taken from a vehicle,350K bounding boxes
        for about 2.3K unique pedestrians.

    -   [INRIA Person
        Dataset](http://pascal.inrialpes.fr/data/human/) – Currently
        one of the most popular pedestrian detection datasets.

    -   [ETH Pedestrian
        Dataset](http://www.vision.ee.ethz.ch/~aess/dataset/) –
        Urban dataset captured from a stereo rig mounted on a
        stroller.

    -   [TUD-Brussels Pedestrian
        Dataset](http://www.d2.mpi-inf.mpg.de/tud-brussels) –
        Dataset with image pairs recorded in an crowded urban
        setting with an onboard camera.

    -   [PASCAL Human
        Detection](http://pascallin.ecs.soton.ac.uk/challenges/VOC/) –
        One of 20 categories in PASCAL VOC detection challenges.

    -   [USC Pedestrian
        Dataset](http://iris.usc.edu/Vision-Users/OldUsers/bowu/DatasetWebpage/dataset.html) –
        Small dataset captured from surveillance cameras.

    Generic Object Recognition

    -   [ImageNet](http://www.image-net.org/) – Currently the
        largest visual recognition dataset in terms of number of
        categories and images.

    -   [Tiny
        Images](http://groups.csail.mit.edu/vision/TinyImages/) – 80
        million 32x32 low resolution images.

    -   [Pascal
        VOC](http://pascallin.ecs.soton.ac.uk/challenges/VOC/) – One
        of the most influential visual recognition datasets.

    -   [Caltech
        101](http://www.vision.caltech.edu/Image_Datasets/Caltech101/) / [Caltech
        256](http://www.vision.caltech.edu/Image_Datasets/Caltech256/) –
        Popular image datasets containing 101 and 256 object
        categories, respectively.

    -   [MIT
        LabelMe](http://new-labelme.csail.mit.edu/Release3.0/index.php) –
        Online annotation tool for building computer vision
        databases.

    Scene Recognition

    -   [MIT SUN Dataset](http://groups.csail.mit.edu/vision/SUN/) –
        MIT scene understanding dataset.

    -   [UIUC Fifteen Scene
        Categories](http://www-cvr.ai.uiuc.edu/ponce_grp/data/) –
        Dataset of 15 natural scene categories.

    Feature Detection and Description

    -   [VGG Affine
        Dataset](http://www.robots.ox.ac.uk/~vgg/data/data-aff.html) –
        Widely used dataset for measuring performance of feature
        detection and description.
        Check[VLBenchmarks](http://www.vlfeat.org/benchmarks/index.html)for
        an evaluation framework.

    Action Recognition

    -   [Benchmarking Activity
        Recognition](http://rogerioferis.com/VisualRecognitionAndSearch/material/LiuFerisSunTutorial.pdf) –
        CVPR 2012 tutorial covering various datasets for action
        recognition.

    RGBD Recognition

    -   [RGB-D Object
        Dataset](http://www.cs.washington.edu/rgbd-dataset/index.html) –
        Dataset containing 300 common household objects

    Reference:

     

    \[1\]: <http://rogerioferis.com/VisualRecognitionAndSearch/Resources.html>


    特征提取

    -   SURF特征: [http://www.vision.ee.ethz.ch/software/index.de.html](http://www.vision.ee.ethz.ch/software/index.de.html(%E5%BD%93%E7%84%B6%E8%BF%99%E5%8F%AA%E6%98%AF%E5%85%B6%E4%B8%AD%E4%B9%8B%E4%B8%80)(当然这只是其中之一)

    -   LBP特征(一种纹理特征):<http://www.comp.hkbu.edu.hk/~icpr06/tutorials/Pietikainen.html>

    -   Fast Corner Detection(OpenCV中的Fast算法):[FAST Corner
        Detection -- Edward
        Rosten](http://mi.eng.cam.ac.uk/~er258/work/fast.html)

    机器视觉

    -   A simple object detector with boosting(Awarded the Best
        Short Course Prize at ICCV
        2005,So了解adaboost的推荐之作):<http://people.csail.mit.edu/torralba/shortCourseRLOC/boosting/boosting.html>

    -   Boosting(该网页上有相当全的Boosting的文章和几个Boosting代码,本人推荐):<http://cbio.mskcc.org/~aarvey/boosting_papers.html>

    -   Adaboost Matlab
        工具:<http://graphics.cs.msu.ru/en/science/research/machinelearning/adaboosttoolbox>

    -   [MultiBoost](http://192.168.1.27/wiki/MultiBoost)(不说啥了,多类Adaboost算法的程序):<http://sourceforge.net/projects/multiboost/>

    -   [TextonBoost](http://192.168.1.27/wiki/TextonBoost)(我们教研室王冠夫师兄的毕设): [Jamie
        Shotton - Code](http://jamie.shotton.org/work/code.html)

    -   [LibSvm](http://192.168.1.27/wiki/LibSvm)的老爹(推荐): <http://www.csie.ntu.edu.tw/~cjlin/>

    -   [Conditional Random
        Fields](http://www.inference.phy.cam.ac.uk/hmw26/crf/)(CRF论文+Code列表,推荐)

    -   [CRF++: Yet Another CRF
        toolkit](http://crfpp.sourceforge.net/)

    -   [Conditional Random Field (CRF) Toolbox for
        Matlab](http://www.computervisiononline.com/software/conditional-random-field-crf-toolbox-matlab)

    -   [Tree CRFs](http://www.cs.cmu.edu/~jkbradle/TreeCRFs/)

    -   [LingPipe:
        Installation](http://alias-i.com/lingpipe/web/install.html)

    -   [Hidden Markov
        Models](http://jedlik.phy.bme.hu/~gerjanos/HMM/node2.html)(推荐)

    -   [隐马尔科夫模型](http://blog.csdn.net/eaglex/article/details/6376826)[(Hidden
        Markov
        Models)](http://blog.csdn.net/eaglex/article/details/6376826)[系列之一](http://blog.csdn.net/eaglex/article/details/6376826)[ -
        eaglex](http://blog.csdn.net/eaglex/article/details/6376826)[的专栏 -
        博客频道 ](http://blog.csdn.net/eaglex/article/details/6376826)[-
        CSDN.NET](http://blog.csdn.net/eaglex/article/details/6376826)[(推荐)](http://blog.csdn.net/eaglex/article/details/6376826)

    综合代码

    -   [CvPapers](http://192.168.1.27/wiki/CvPapers)(好吧,牛吧网站,里面有ICCV,CVPR,ECCV,SIGGRAPH的论文收录,然后还有一些论文的代码搜集,要求加精!):<http://www.cvpapers.com/>

    -   Computer Vision
        Software(里面代码很多,并详细的给出了分类):<http://peipa.essex.ac.uk/info/software.html>

    -   某人的Windows
        Live(我看里面东东不少就收藏了):<https://skydrive.live.com/?cid=3b6244088fd5a769#cid=3B6244088FD5A769&id=3B6244088FD5A769!523>

    -   MATLAB and Octave Functions for Computer Vision and Image
        Processing(这个里面的东西也很全,只是都是用Matlab和Octave开发的):<http://www.csse.uwa.edu.au/~pk/research/matlabfns/>

    -   Computer Vision
        Resources(里面的视觉算法很多,给出了相应的论文和Code,挺好的):<https://netfiles.uiuc.edu/jbhuang1/www/resources/vision/index.html>

    -   MATLAB Functions for Multiple View
        Geometry(关于物体多视角计算的库):<http://www.robots.ox.ac.uk/~vgg/hzbook/code/>

    -   Evolutive Algorithm based on Naïve Bayes models
        Estimation(单独列了一个算法的Code):<http://www.cvc.uab.cat/~xbaro/eanbe/#_Software>

    主页代码

    -   [Pablo Negri's Home
        Page](http://pablonegri.free.fr/index.html)

    -   [Jianxin Wu's
        homepage](http://c2inet.sce.ntu.edu.sg/Jianxin/index.html)

    -   [Peter Carbonetto](http://www.cs.ubc.ca/~pcarbo/)

    -   [Markov Random Fields for
        Super-Resolution](http://people.csail.mit.edu/billf/project%20pages/sresCode/Markov%20Random%20Fields%20for%20Super-Resolution.html)

    -   [Detecting and Sketching the
        Common](http://www.wisdom.weizmann.ac.il/~vision/SketchTheCommon/)

    -   [Pedro Felzenszwalb](http://people.cs.uchicago.edu/~pff/)

    -   [Hae JONG,
        SEO](http://users.soe.ucsc.edu/~rokaf/interests.html)

    -   [CAP 5416 - Computer
        Vision](http://www.cise.ufl.edu/class/cap5416fa09/Projects.html)

    -   [Parallel Tracking and Mapping for Small AR Workspaces
        (PTAM)](http://www.robots.ox.ac.uk/~gk/PTAM/)

    -   [Deva Ramanan - UC Irvine - Computer
        Vision](http://www.ics.uci.edu/~dramanan/)

    -   [Raghuraman Gopalan](http://www.umiacs.umd.edu/~raghuram/)

    -   [Hui Kong](http://bmi.osu.edu/~hkong/index.htm)

    -   [Jamie Shotton - Post-Doctoral Researcher in Computer
        Vision](http://jamie.shotton.org/work/index.html)

    -   [Jean-Yves
        AUDIBERT](http://imagine.enpc.fr/~audibert/index.html)

    -   [Olga Veksler](http://www.csd.uwo.ca/~olga/)

    -   [Stephen
        Gould](http://users.cecs.anu.edu.au/~sgould/index.html#software)

    -   [Publications (Last Update:
        09/30/10)](http://faculty.ucmerced.edu/mhyang/code.html)

    -   [Karim Ali -
        FlowBoost](http://cvlab.epfl.ch/~ali/flowboost.htm)

    -   [A simple parts and structure object
        detector](http://people.csail.mit.edu/fergus/iccv2005/partsstructure.html)

    -   [Code - Oxford Brookes Vision
        Group](http://cms.brookes.ac.uk/research/visiongroup/code.php)

    -   [Taku Kudo](http://chasen.org/~taku/index.html.en)

    行人检测

    -   [Histogram of Oriented Gradient
        (Windows)](http://www.computing.edu.au/~12482661/hog.html)

    -   [INRIA Pedestrian
        detector](http://www.cs.berkeley.edu/~smaji/projects/ped-detector/)

    -   [Poselets](http://www.eecs.berkeley.edu/~lbourdev/poselets/)

    -   [William Robson Schwartz -
        Softwares](http://www.liv.ic.unicamp.br/~wschwartz/softwares.html)

    -   [calvin upper-body detector
        v1.02](http://www.vision.ee.ethz.ch/~calvin/calvin_upperbody_detector/)

    -   [RPT@CVG](http://www.cvg.rdg.ac.uk/software/rpt/index.html)

    -   [Main
        Page](http://www.idiap.ch/~odobez/human-detection/index.html)

    -   [Source
        Code](http://www.lienhart.de/Source_Code/source_code.html)

    -   [Dr. Luciano
        Spinello](http://www.informatik.uni-freiburg.de/~spinello/people2D.html)

    -   [Pedestrian
        Detection](http://bmi.osu.edu/~hkong/Human_Detection.html)

    -   [Class-Specific Hough Forests for Object
        Detection](http://www.vision.ee.ethz.ch/~gallju/projects/houghforest/index.html)

    -   [Jianxin Wu's
        homepage](http://c2inet.sce.ntu.edu.sg/Jianxin/index.html)(就是上面的)

    -   Berkeley大学做的Pedestrian
        Detector,使用交叉核的支持向量机,特征使用HOG金字塔,提供Matlab和C++混编的代码:<http://www.cs.berkeley.edu/~smaji/projects/ped-detector/>

    视觉壁障

    -   [High Speed Obstacle Avoidance using Monocular Vision and
        Reinforcement
        Learning](http://www.cs.cornell.edu/~asaxena/rccar/)

    -   [TLD](http://info.ee.surrey.ac.uk/Personal/Z.Kalal/tld.html)(2010年很火的tracking算法)

    -   [online boosting
        trackers](http://www.vision.ee.ethz.ch/boostingTrackers/)

    -   [Boris
        Babenko](http://vision.ucsd.edu/~bbabenko/project_miltrack.shtml)

    -   Optical Flow Algorithm Evaluation
        (提供了一个动态贝叶斯网络框架,例如递
        归信息处理与分析、卡尔曼滤波、粒子滤波、序列蒙特卡罗方法等,C++写的)[http://of-eval.sourceforge.net/](http://of-.sourceforge.net/)

    物体检测算法

    -   [Object
        Detection](http://www.irisa.fr/vista/Equipe/People/Laptev/objectdetection.html)

    -   [Software for object
        detection](http://www.seas.upenn.edu/~limingw/obj_det_accv07/code.html)

    人脸检测

    -   [Source
        Code](http://www.lienhart.de/Source_Code/source_code.html)

    -   [10个人脸检测项目](http://itp.nyu.edu/~mbe230/blogmer/2011/02/10-face-detection-projects/)

    -   [Jianxin Wu's
        homepage](http://c2inet.sce.ntu.edu.sg/Jianxin/index.html)(又是这货)

    ICA独立成分分析

    -   [An ICA page-papers,code,demo,links (Tony
        Bell)](http://cnl.salk.edu/~tony/ica.html)

    -   [FastICA](http://research.ics.tkk.fi/ica/fastica/)

    -   [Cached k-d tree search for ICP
        algorithms](http://kos.informatik.uni-osnabrueck.de/download/3dim2007/paper.html)

    滤波算法

    -   卡尔曼滤波:[The Kalman
        Filter](http://www.cs.unc.edu/~welch/kalman/index.html)(终极网页)

    -   Bayesian Filtering Library: [The Bayesian Filtering
        Library](http://www.orocos.org/bfl)

    路面识别

    -   [Source
        Code](http://www.multimedia-computing.de/wiki/Source_Code#Dataset_of_logos_in_real-world_images:_FlickrLogos-32)

    -   [Vanishing point detection for general road
        detection](http://bmi.osu.edu/~hkong/Road_Detection.html)

    分割算法

    -   MATLAB Normalized Cuts Segmentation
        Code:[software](http://www.cis.upenn.edu/~jshi/software/)

    -   超像素分割:[SLIC
        Superpixels](http://ivrg.epfl.ch/supplementary_material/RK_SLICSuperpixels/index.html)

    -   

附: http://blog.sina.com.cn/s/blog_5086c3e20101kdy5.htmlhttp://www.yuanyong.org/cv/cv-code-three.html

参考:

 

http://blog.csdn.net/carson2005/article/details/6601109

http://blog.csdn.net/chlele0105/article/details/16880049

http://blog.csdn.net/yihaizhiyan/article/details/6583727

http://www.sigvc.org/bbs/forum.phpmod=viewthread&tid=3126&highlight=%BC%C6%CB%E3%BB%FA%CA%D3%BE%F5%B4%FA%C2%EB

会聚不完善,欢迎补全!!更多,请关注http://blog.csdn.net/tiandijun/

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