Awesome-People-in-Computer-Vision
by solarlee
AI summary
CV researchers
A curated list of influential computer vision researchers and their contributions to the field.
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What's in the list
561 links in 46 sections, with live GitHub stats.activeno commit in 2y
Links
- William T. Freeman
(MIT)
William T. Freeman
- Taeg Sang ("Tim") Cho
(Wilmer Hale)
- Roger Grosse
(University of Toronto)
- Biliana Kaneva
(MIT)
- Ce Liu
(Google Research)
- Michael Rubinstein
(Google Research)
- Bryan Russell
(Adobe Research)
- Erik B. Sudderth
(Brown University)
- Marshall Tappen
(Amazon)
Links
- Eero Simoncelli
(NYU)
- Yair Weiss
(The Hebrew University of Jerusalem)
Yair Weiss
- Anat Levin
(The Weizmann Institute of Science)
Links
- Ron Dror
(Stanford University)
- Roland Fleming
(University of Giessen)
- Marshall Tappen
(Amazon)
- Josh McDermott
(MIT)
- Lavanya Sharan
(MIT)
- Ce Liu
(Google Research)
- Rodney Brooks
(MIT)
- David Lowe
(University of British Columbia)
- David Kriegman
(UCSD)
- Jitendra Malik
(UC Berkeley)
Jitendra Malik
- Paul Kube
(UCSD)
- Pietro Perona
(Caltech)
- Clark F. Olson
(University of Washington, Bothell)
- Ruth Rosenholtz
(MIT)
- Paul Debevec
(USC)
- Christoph Bregler
(Facebook/Oculus)
- Jianbo Shi
(University of Pennsylvania)
- Yizhou Yu
(The University of Hong Kong)
- Serge J. Belongie
(Cornell Tech)
Jitendra Malik / Serge J. Belongie
- Piotr Dollár
(Facebook AI Research)
- Tsung-Yi Lin
(Cornell Tech)
Jitendra Malik
- Alexei A. Efros
(UC Berkeley)
Jitendra Malik / Alexei A. Efros
- Derek Hoiem
(UIUC)
- James Hays
(Brown University)
- Jean-François Lalonde
(Laval University)
- Tomasz Malisiewicz
(VISION.AI, LLC)
- Santosh Divvala
(Allen Institute for Artificial Intelligence)
Jitendra Malik
- Greg Mori
(Simon Fraser University)
- Charless C. Fowlkes
(UC Irvine)
- Arie E. Kaufman
(Stonybrook University)
- Xiaofeng Ren
(Amazon)
- Subhransu Maji
(University of Massachusetts, Amherst)
- Lubomir Bourdev
(Facebook AI Research)
Links
- Michael Kass
(Pixar Research Group)
- Sheng-Jyh Wang
(National Chiao Tung University)
- Mohamed Abdel-Mottaleb
(University of Miami)
- Narendra Ahuja
(UIUC)
Narendra Ahuja
- Ming-Hsuan Yang
(UC Merced)
Links
- Rama Chellappa
(University of Maryland)
- Larry S. Davis
(University of Maryland)
- Sven Dickinson
(University of Toronto)
- David S. Doermann
(University of Maryland)
- Zoran Duric
(George Mason University)
- Charles R. Dyer
(University of Wisconsin - Madison)
Charles R. Dyer
- Steven Seitz
(University of Washington)
Charles R. Dyer / Steven Seitz
- Noah Snavely
(Cornell University/Google)
- Li Zhang
(Google)
- Jovan Popović
(Adobe Research)
- Daniel Goldman
(Adobe)
Links
- Jan-Olof Eklundh
(KTH - Royal Institute of Technology)
- Shmuel Peleg
(The Hebrew University of Jerusalem)
Shmuel Peleg
- Haim Schweitzer
(The University of Texas at Dallas)
- Michael Werman
(The Hebrew University of Jerusalem)
- Daniel Keren
(Haifa University)
- Yacov Hel-Or
(The Interdisciplinary Center)
- Michal Irani
(The Weizmann Institute of Science)
Shmuel Peleg / Michal Irani
- Eli Shechtman
(Adobe Research)
Shmuel Peleg
- Hagit Zabrodsky (Hel-Or)
(University of Haifa)
- Moshe Ben-Ezra
(MIT Media Lab)
- Yael Pritch
(Google [X])
Links
- Matti Pietikäinen
(University of Oulu)
- Zygmunt Pizlo
(Purdue University)
- Zhengyou Zhang
(Microsoft Research)
- Pascal Fua
(EPFL)
- Martial Hebert
(CMU)
Martial Hebert
- Andrew Johnson
(JPL)
Links
- Michael Leventon
(D. E. Shaw & Co.)
- Jonathan Touboul
(Collège de France and INRIA Paris-Rocquencourt)
- Jean Ponce
(Ecole Normale Supérieure)
Jean Ponce
- Yasutaka Furukawa
(Washington University in St. Louis)
- Oliver Whyte
(Microsoft)
- Y-Lan Boureau
(NYU)
- Olivier Duchenne
(Inter Korea)
- Armand Joulin
(Facebook AI Research)
- Svetlana Lazebnik
(UIUC)
Jean Ponce / Svetlana Lazebnik
- Joseph Tighe
(Amazon)
- Yunchao Gong
(Facebook AI Research)
Links
- Peter N. Belhumeur
(Columbia University/Dropbox)
Peter N. Belhumeur
- Todd Zickler
(Harvard University)
Peter N. Belhumeur / Todd Zickler
- Ayan Chakrabarti
(Toyota Technological Institute at Chicago)
- Sanjeev Koppal
(University of Florida)
Peter N. Belhumeur
- Neeraj Kumar
(Dropbox)
Links
- Trevor Darrell
(UC Berkeley)
Trevor Darrell
- Gregory Shakhnarovich
(Toyota Technological Institute at Chicago)
- Kristen Grauman
(UT Austin)
Trevor Darrell / Kristen Grauman
- Adriana Kovashka
(University of Pittsburgh)
- Sung Ju Hwang
(Ulsan National Institute of Science and Technology)
- Jaechul Kim
(Amazon Research)
- Yong Jae Lee
(UC Davis)
- Sudheendra Vijayanarasimhan
(Google Research)
Trevor Darrell
- Kate Saenko
(UMass Lowell)
Links
- Irfan Essa
(Georgia Institute of Technology)
- Tony Jebara
(Columbia University)
- Baback Moghaddam
(JPL)
- Rosalind Picard
(MIT Media Lab)
- Stanley Sclaroff
(Boston University)
- Thad Starner
(Georgia Institute of Technology)
- Matthew Turk
(University of California, Santa Barbara)
- Natasha Gelfand
(Nokia Research)
- Augusto Roman
(Flux Factory)
- Li-Yi Wei
(The University of Hong Kong)
- Szymon Rusinkeiwicz
(Princeton University)
- Brian Curless
(University of Washington)
Brian Curless
- Li Zhang
(Google)
- Yung-Yu Chuang
(National Taiwan University)
- Daniel Goldman
(Adobe)
Links
- Philippe Lacroute
(Stanford University)
Books
- Computer Vision: Models, Learning, and Inference
Simon J. D. Prince 2012
- Computer Vision: Theory and Application
Rick Szeliski 2010
- Computer Vision: A Modern Approach (2nd edition)
David Forsyth and Jean Ponce 2011
- Multiple View Geometry in Computer Vision
Richard Hartley and Andrew Zisserman 2004
- Computer Vision
Linda G. Shapiro 2001
- Vision Science: Photons to Phenomenology
Stephen E. Palmer 1999
- Visual Object Recognition synthesis lecture
Kristen Grauman and Bastian Leibe 2011
- Computer Vision for Visual Effects
Richard J. Radke, 2012
- High dynamic range imaging: acquisition, display, and image-based lighting
Reinhard, E., Heidrich, W., Debevec, P., Pattanaik, S., Ward, G., Myszkowski, K 2010
- Learning OpenCV: Computer Vision with the OpenCV Library
Gary Bradski and Adrian Kaehler
- Practical Python and OpenCV
Adrian Rosebrock
- OpenCV Essentials
Oscar Deniz Suarez, Mª del Milagro Fernandez Carrobles, Noelia Vallez Enano, Gloria Bueno Garcia, Ismael Serrano Gracia
- Pattern Recognition and Machine Learning
Christopher M. Bishop 2007
- Neural Networks for Pattern Recognition
Christopher M. Bishop 1995
- Probabilistic Graphical Models: Principles and Techniques
Daphne Koller and Nir Friedman 2009
- Pattern Classification
Peter E. Hart, David G. Stork, and Richard O. Duda 2000
- Machine Learning
Tom M. Mitchell 1997
- Gaussian processes for machine learning
Carl Edward Rasmussen and Christopher K. I. Williams 2005
- Learning From Data
Yaser S. Abu-Mostafa, Malik Magdon-Ismail and Hsuan-Tien Lin 2012
- Neural Networks and Deep Learning
Michael Nielsen 2014
- Bayesian Reasoning and Machine Learning
David Barber, Cambridge University Press, 2012
- Linear Algebra and Its Applications
Gilbert Strang 1995
Courses
- EENG 512 / CSCI 512 - Computer Vision
William Hoff (Colorado School of Mines)
- Visual Object and Activity Recognition
Alexei A. Efros and Trevor Darrell (UC Berkeley)
- Computer Vision
Steve Seitz (University of Washington)
- Visual Recognition
Kristen Grauman (UT Austin)
- Language and Vision
Tamara Berg (UNC Chapel Hill)
- Convolutional Neural Networks for Visual Recognition
Fei-Fei Li and Andrej Karpathy (Stanford University)
- Computer Vision
Rob Fergus (NYU)
- Computer Vision
Derek Hoiem (UIUC)
- Computer Vision: Foundations and Applications
Kalanit Grill-Spector and Fei-Fei Li (Stanford University)
- High-Level Vision: Behaviors, Neurons and Computational Models
Fei-Fei Li (Stanford University)
- Advances in Computer Vision
Antonio Torralba and Bill Freeman (MIT)
- Computer Vision
Bastian Leibe (RWTH Aachen University)
- Computer Vision 2
Bastian Leibe (RWTH Aachen University)
- Image Manipulation and Computational Photography
Alexei A. Efros (UC Berkeley)
- Computational Photography
Alexei A. Efros (CMU)
- Computational Photography
Derek Hoiem (UIUC)
- Computational Photography
James Hays (Brown University)
- Digital & Computational Photography
Fredo Durand (MIT)
- Computational Camera and Photography
Ramesh Raskar (MIT Media Lab)
- Computational Photography
Irfan Essa (Georgia Tech)
- Courses in Graphics
Stanford University
- Computational Photography
Rob Fergus (NYU)
- Introduction to Visual Computing
Kyros Kutulakos (University of Toronto)
- Computational Photography
Kyros Kutulakos (University of Toronto)
- Computer Vision for Visual Effects
Rich Radke (Rensselaer Polytechnic Institute)
- Introduction to Image Processing
Rich Radke (Rensselaer Polytechnic Institute)
- Machine Learning
Andrew Ng (Stanford University)
- Learning from Data
Yaser S. Abu-Mostafa (Caltech)
- Statistical Learning
Trevor Hastie and Rob Tibshirani (Stanford University)
- Statistical Learning Theory and Applications
Tomaso Poggio, Lorenzo Rosasco, Carlo Ciliberto, Charlie Frogner, Georgios Evangelopoulos, Ben Deen (MIT)
- Statistical Learning
Genevera Allen (Rice University)
- Practical Machine Learning
Michael Jordan (UC Berkeley)
- Course on Information Theory, Pattern Recognition, and Neural Networks
David MacKay (University of Cambridge)
- Methods for Applied Statistics: Unsupervised Learning
Lester Mackey (Stanford)
- Machine Learning
Andrew Zisserman (University of Oxford)
- Convex Optimization I
Stephen Boyd (Stanford University)
- Convex Optimization II
Stephen Boyd (Stanford University)
- Convex Optimization
Stephen Boyd (Stanford University)
- Optimization at MIT
(MIT)
- Convex Optimization
Ryan Tibshirani (CMU)
Papers
- CVPapers
Computer vision papers on the web
- SIGGRAPH Paper on the web
Graphics papers on the web
- NIPS Proceedings
NIPS papers on the web
- Annotated Computer Vision Bibliography
Keith Price (USC)
Tutorials and talks
- Computer Vision Talks
Lectures, keynotes, panel discussions on computer vision
- The Three R's of Computer Vision
Jitendra Malik (UC Berkeley) 2013
- Applications to Machine Vision
Andrew Blake (Microsoft Research) 2008
- The Future of Image Search
Jitendra Malik (UC Berkeley) 2008
- Should I do a PhD in Computer Vision?
Fatih Porikli (Australian National University)
- CVPR 2015
Jun 2015
- ECCV 2014
Sep 2014
- CVPR 2014
Jun 2014
- ICCV 2013
Dec 2013
- ICML 2013
Jul 2013
- CVPR 2013
Jun 2013
- ECCV 2012
Oct 2012
- ICML 2012
Jun 2012
- CVPR 2012
Jun 2012
- 3D Computer Vision: Past, Present, and Future
Steve Seitz (University of Washington) 2011
- Reconstructing the World from Photos on the Internet
Steve Seitz (University of Washington) 2013
- The Distributed Camera
Noah Snavely (Cornell University) 2011
- Planet-Scale Visual Understanding
Noah Snavely (Cornell University) 2014
- A Trillion Photos
Steve Seitz (University of Washington) 2013
- Reflections on Image-Based Modeling and Rendering
Richard Szeliski (Microsoft Research) 2013
- Photographing Events over Time
William T. Freeman (MIT) 2011
- Old and New algorithm for Blind Deconvolution
Yair Weiss (The Hebrew University of Jerusalem) 2011
- A Tour of Modern "Image Processing"
Peyman Milanfar (UC Santa Cruz/Google) 2010
- Topics in image and video processing
Andrew Blake (Microsoft Research) 2007
- Computational Photography
William T. Freeman (MIT) 2012
- Revealing the Invisible
Frédo Durand (MIT) 2012
- Overview of Computer Vision and Visual Effects
Rich Radke (Rensselaer Polytechnic Institute) 2014
- Where machine vision needs help from machine learning
William T. Freeman (MIT) 2011
- Learning in Computer Vision
Simon Lucey (CMU) 2008
- Learning and Inference in Low-Level Vision
Yair Weiss (The Hebrew University of Jerusalem) 2009
- Object Recognition
Larry Zitnick (Microsoft Research)
- Generative Models for Visual Objects and Object Recognition via Bayesian Inference
Fei-Fei Li (Stanford University)
- Graphical Models for Computer Vision
Pedro Felzenszwalb (Brown University) 2012
- Graphical Models
Zoubin Ghahramani (University of Cambridge) 2009
- Machine Learning, Probability and Graphical Models
Sam Roweis (NYU) 2006
- Graphical Models and Applications
Yair Weiss (The Hebrew University of Jerusalem) 2009
- A Gentle Tutorial of the EM Algorithm
Jeff A. Bilmes (UC Berkeley) 1998
- Introduction To Bayesian Inference
Christopher Bishop (Microsoft Research) 2009
- Support Vector Machines
Chih-Jen Lin (National Taiwan University) 2006
- Bayesian or Frequentist, Which Are You?
Michael I. Jordan (UC Berkeley)
- Optimization Algorithms in Machine Learning
Stephen J. Wright (University of Wisconsin-Madison)
- Convex Optimization
Lieven Vandenberghe (University of California, Los Angeles)
- Continuous Optimization in Computer Vision
Andrew Fitzgibbon (Microsoft Research)
- Beyond stochastic gradient descent for large-scale machine learning
Francis Bach (INRIA)
- Variational Methods for Computer Vision
Daniel Cremers (Technische Universität München) ( )
- A tutorial on Deep Learning
Geoffrey E. Hinton (University of Toronto)
- Deep Learning
Ruslan Salakhutdinov (University of Toronto)
- Scaling up Deep Learning
Yoshua Bengio (University of Montreal)
- ImageNet Classification with Deep Convolutional Neural Networks
Alex Krizhevsky (University of Toronto)
- The Unreasonable Effectivness Of Deep Learning
Yann LeCun (NYU/Facebook Research) 2014
- Deep Learning for Computer Vision
Rob Fergus (NYU/Facebook Research)
- High-dimensional learning with deep network contractions
Stéphane Mallat (Ecole Normale Superieure)
- Machine Learning Summer School
Reykjavik, Iceland 2014
Tutorials and talks / Machine Learning Summer School
- Deep Learning Session 1
Yoshua Bengio (Universtiy of Montreal)
- Deep Learning Session 2
Yoshua Bengio (University of Montreal)
- Deep Learning Session 3
Yoshua Bengio (University of Montreal)
Software
- Computer Vision Resources
Jia-Bin Huang (UIUC)
- Source Code Collection for Reproducible Research
Xin Li (West Virginia University)
- OpenGV
geometric computer vision algorithms
- MinimalSolvers
Minimal problems solver
- openMVG: open Multiple View Geometry
Multiple View Geometry; Structure from Motion library & softwares
- Coarse2Fine Optical Flow
Ce Liu (MIT)
- GTSAM: General smoothing and mapping library for Robotics and SFM
-- Georgia Institute of Technology
- FabMap: appearance-based loop closure system
also available in
- Geometric Context
Derek Hoiem (CMU)
- Recovering Spatial Layout
Varsha Hedau (UIUC)
- Geometric Reasoning
David C. Lee (CMU)
RGBD2Full3D
Ruiqi Guo (UIUC)
- Ceres Solver
Nonlinear least-square problem and unconstrained optimization solver
- NLopt
Nonlinear least-square problem and unconstrained optimization solver
- OpenGM
Factor graph based discrete optimization and inference solver
- GTSAM
Factor graph based lease-square optimization solver
Open source Python module for computer vision
ccv: A Modern Computer Vision Library
Local Binary Patterns
HDR_Toolbox
SEEDS Revised
Fast Edge Detection Using Structured Forests
KFusion: Implementation of KinectFusion
kinfu_remake: Lightweight, reworked and optimized version of Kinfu.
VoxelHashing: Large-scale KinectFusion
SVO: Semi-direct visual odometry
DVO: dense visual odometry
G2O: General framework for graph optomization
ORB-SLAM
SPP-Net
PMBP: PatchMatch Belief Propagation
NeuralTalk
Awesome Deep Vision
Awesome Machine LearningDatasets
- CV Datasets on the web
CVPapers
- Are we there yet?
Which paper provides the best results on standard dataset X?
NYU depth v2 - Indoor Segmentation and Support Inference from RGBD Images / Resources for students
- Resources for students
Frédo Durand (MIT)
- Advice for Graduate Students
Aaron Hertzmann (Adobe Research)
- Graduate Skills Seminars
Yashar Ganjali, Aaron Hertzmann (University of Toronto)
- Research Skills
Simon Peyton Jones (Microsoft Research)
- Resource collection
Tao Xie (UIUC) and Yuan Xie (UCSB)
- Write Good Papers
Frédo Durand (MIT)
- Notes on writing
Frédo Durand (MIT)
- How to Write a Bad Article
Frédo Durand (MIT)
- How to write a good CVPR submission
William T. Freeman (MIT)
- How to write a great research paper
Simon Peyton Jones (Microsoft Research)
- How to write a SIGGRAPH paper
SIGGRAPH ASIA 2011 Course
- Writing Research Papers
Aaron Hertzmann (Adobe Research)
- How to Write a Paper for SIGGRAPH
Jim Blinn
- How to Get Your SIGGRAPH Paper Rejected
Jim Kajiya (Microsoft Research)
- How to write a SIGGRAPH paper
Li-Yi Wei (The University of Hong Kong)
- How to Write a Great Paper
Martin Martin Hering Hering--Bertram (Hochschule Bremen University of Applied Sciences)
- How to have a paper get into SIGGRAPH?
Takeo Igarashi (The University of Tokyo)
- Good Writing
Marc H. Raibert (Boston Dynamics, Inc.)
- How to Write a Computer Vision Paper
Derek Hoiem (UIUC)
- Common mistakes in technical writing
Wojciech Jarosz (Dartmouth College)
- Giving a Research Talk
Frédo Durand (MIT)
- How to give a good talk
David Fleet (University of Toronto) and Aaron Hertzmann (Adobe Research)
- Designing conference posters
Colin Purrington
- How to do research
William T. Freeman (MIT)
- You and Your Research
Richard Hamming
- Seven Warning Signs of Bogus Science
Robert L. Park
- Five Principles for Choosing Research Problems in Computer Graphics
Thomas Funkhouser (Cornell University)
- How To Do Research In the MIT AI Lab
David Chapman (MIT)
- Recent Advances in Computer Vision
Ming-Hsuan Yang (UC Merced)
- How to Come Up with Research Ideas in Computer Vision?
Jia-Bin Huang (UIUC)
- How to Read Academic Papers
Jia-Bin Huang (UIUC)
- Time Management
Randy Pausch (CMU)
NYU depth v2 - Indoor Segmentation and Support Inference from RGBD Images / Blogs
- Learn OpenCV
Satya Mallick
- Tombone's Computer Vision Blog
Tomasz Malisiewicz
- Computer vision for dummies
Vincent Spruyt
- Andrej Karpathy blog
Andrej Karpathy
- AI Shack
Utkarsh Sinha
- Computer Vision Talks
Eugene Khvedchenya
NYU depth v2 - Indoor Segmentation and Support Inference from RGBD Images / Links
- The Computer Vision Industry
David Lowe
awesome-deep-learningNYU depth v2 - Indoor Segmentation and Support Inference from RGBD Images / Songs
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