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Awesome Computer Vision
A curated list of awesome computer vision resources
Here you can see meta information about this topic like the time we last updated this page, the original creator of the awesome list and a link to the original GitHub repository.
Thank you jbhuang0604 & contributors
View Topic on GitHub:
jbhuang0604/awesome-computer-vision
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Simply type in what you are looking for and the results will be filtered on the fly.
Further filter the resources on this page by type (repository/other resource), number of stars on GitHub and time of last commit in months.
Computer Vision
Simon J. D. Prince 2012
David Forsyth and Jean Ponce 2011
Richard Hartley and Andrew Zisserman 2004
Stephen E. Palmer 1999
Kristen Grauman and Bastian Leibe 2011
Reinhard, E., Heidrich, W., Debevec, P., Pattanaik, S., Ward, G., Myszkowski, K 2010
OpenCV Programming
Gary Bradski and Adrian Kaehler
Oscar Deniz Suarez, Mª del Milagro Fernandez Carrobles, Noelia Vallez Enano, Gloria Bueno Garcia, Ismael Serrano Gracia
Machine Learning
Christopher M. Bishop 2007
Christopher M. Bishop 1995
Daphne Koller and Nir Friedman 2009
Peter E. Hart, David G. Stork, and Richard O. Duda 2000
Carl Edward Rasmussen and Christopher K. I. Williams 2005
David Barber, Cambridge University Press, 2012
Fundamentals
Gilbert Strang 1995
Computer Vision
William Hoff (Colorado School of Mines)
Alexei A. Efros and Trevor Darrell (UC Berkeley)
Steve Seitz (University of Washington)
Fall 2016](http://vision.cs.utexas.edu/381V-fall2016/) - Kristen Grauman (UT Austin)
Kalanit Grill-Spector and Fei-Fei Li (Stanford University)
Fei-Fei Li (Stanford University)
Antonio Torralba and Bill Freeman (MIT)
Computational Photography
Alexei A. Efros (UC Berkeley)
Fredo Durand (MIT)
Ramesh Raskar (MIT Media Lab)
Kyros Kutulakos (University of Toronto)
Kyros Kutulakos (University of Toronto)
Rich Radke (Rensselaer Polytechnic Institute)
Rich Radke (Rensselaer Polytechnic Institute)
Machine Learning and Statistical Learning
Trevor Hastie and Rob Tibshirani (Stanford University)
Tomaso Poggio, Lorenzo Rosasco, Carlo Ciliberto, Charlie Frogner, Georgios Evangelopoulos, Ben Deen (MIT)
Michael Jordan (UC Berkeley)
David MacKay (University of Cambridge)
Lester Mackey (Stanford)
Andrew Zisserman (University of Oxford)
Sebastian Thrun (Stanford University)
Charles Isbell, Michael Littman (Georgia Tech)
Fei-Fei Li, Andrej Karphaty, Justin Johnson (Stanford University)
Rudolph Triebel (TU Munich)
Optimization
Stephen Boyd (Stanford University)
Conference papers on the web
Keith Price (USC)
Survey Papers
Computer Vision
Lectures, keynotes, panel discussions on computer vision
Jitendra Malik (UC Berkeley) 2013
Andrew Blake (Microsoft Research) 2008
Jitendra Malik (UC Berkeley) 2008
Fatih Porikli (Australian National University)
Recent Conference Talks
3D Computer Vision
Steve Seitz (University of Washington) 2011
Steve Seitz (University of Washington) 2013
Internet Vision
Noah Snavely (Cornell University) 2011
Noah Snavely (Cornell University) 2014
Steve Seitz (University of Washington) 2013
Computational Photography
Richard Szeliski (Microsoft Research) 2013
William T. Freeman (MIT) 2011
Yair Weiss (The Hebrew University of Jerusalem) 2011
Peyman Milanfar (UC Santa Cruz/Google) 2010
Andrew Blake (Microsoft Research) 2007
Rich Radke (Rensselaer Polytechnic Institute) 2014
Learning and Vision
William T. Freeman (MIT) 2011
Yair Weiss (The Hebrew University of Jerusalem) 2009
Object Recognition
Fei-Fei Li (Stanford University)
Graphical Models
Pedro Felzenszwalb (Brown University) 2012
Zoubin Ghahramani (University of Cambridge) 2009
Sam Roweis (NYU) 2006
Yair Weiss (The Hebrew University of Jerusalem) 2009
Machine Learning
Jeff A. Bilmes (UC Berkeley) 1998
Christopher Bishop (Microsoft Research) 2009
Chih-Jen Lin (National Taiwan University) 2006
Michael I. Jordan (UC Berkeley)
Optimization
Stephen J. Wright (University of Wisconsin-Madison)
Lieven Vandenberghe (University of California, Los Angeles)
Andrew Fitzgibbon (Microsoft Research)
Francis Bach (INRIA)
Daniel Cremers (Technische Universität München) (lecture 18 missing from playlist)
Deep Learning
Geoffrey E. Hinton (University of Toronto)
Ruslan Salakhutdinov (University of Toronto)
Yoshua Bengio (University of Montreal)
Alex Krizhevsky (University of Toronto)
Yann LeCun (NYU/Facebook Research) 2014
Rob Fergus (NYU/Facebook Research)
Stéphane Mallat (Ecole Normale Superieure)
IPAM, 2012
Reykjavik, Iceland 2014
Yoshua Bengio (Universtiy of Montreal)
Yoshua Bengio (University of Montreal)
Yoshua Bengio (University of Montreal)
Annotation tools
External Resource Links
Xin Li (West Virginia University)
General Purpose Computer Vision Library
Open source Python module for computer vision
C-based/Cached/Core Computer Vision Library, A Modern Computer Vision Library
An open source computer vision framework that gives access to several high-powered computer vision libraries, such as OpenCV. Written on Python and runs on Mac, Windows, and Ubuntu Linux.
VLFeat is an open and portable library of computer vision algorithms, which has Matlab toolbox.
Multiple-view Computer Vision
A curated list of papers & resources linked to 3D reconstruction from images.
Multiple View Geometry; Structure from Motion library & softwares
Feature Detection and Extraction
C++ implementation of the Local Binary Pattern texture descriptors. This class integrates with OpenCV and FFTW3 to bring a complete and fast implementation of the popular descriptors: LBP u2, ri, riu2 & hf. The routines for calculating these descriptors are inspired by the Matlab code of the original authors.
VLFeat is an open and portable library of computer vision algorithms, which has Matlab toolbox.
High Dynamic Range Imaging
HDR Toolbox for processing High Dynamic Range (HDR) images into MATLAB and Octave
Semantic Segmentation
Stereo Vision
Optical Flow
Super-resolution
Image Deblurring
Image Completion
Image Retargeting
Alpha Matting
Image Pyramid
Edge-preserving image processing
Intrinsic Images
Contour Detection and Image Segmentation
Implementation of the superpixel algorithm called SEEDS [1].
Structured Edge Detection Toolbox
Interactive Image Segmentation
Video Segmentation
Camera calibration
SLAM community:
Tracking/Odometry:
This is an implementation sketch of the KinectFusion system described by Newcombe et al.
Optimized and reworked version of Kinfu
[Siggraph Asia 2013] Large-Scale, Real-Time 3D Reconstruction
Semi-direct Visual Odometry
Dense Visual Odometry and SLAM
Graph Optimization:
g2o: A General Framework for Graph Optimization
Georgia Institute of Technology
Loop Closure:
also available in OpenCV2.4.11
Localization & Mapping:
LSD-SLAM
A Versatile and Accurate Monocular SLAM
Single-view Spatial Understanding
Matlab codes that convert a RGBD image into a cad like model. This code is released as a part of my PhD dissertation.
Object Detection
Object detection system using deformable part models (DPMs) and latent SVM (voc-release5). You may want to use the latest tarball on my website. The github code may include code changes that have not been tested as thoroughly and will not necessarily reproduce the results on the website.
R-CNN: Regions with Convolutional Neural Network Features
SPP_net : Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
Structured Edge Detection Toolbox
General purpose nearest neighbor search
Nearest Neighbor Field Estimation
Visual Tracking
Image Captioning
Optimization
C++ library for modeling and solving large complicated nonlinear least squares problems from google. [BSD]
Nonlinear least-square problem and unconstrained optimization solver
Factor graph based discrete optimization and inference solver
Deep Learning
A curated list of deep learning resources for computer vision
Machine Learning
A curated list of awesome Machine Learning frameworks, libraries and software.
External Dataset Link Collection
Which paper provides the best results on standard dataset X?
Stereo Vision
Optical Flow
Video Object Segmentation
Change Detection
Image Super-resolutions
Intrinsic Images
Material Recognition
Multi-view Reconsturction
Visual Tracking
Visual Surveillance
Change detection
Image Classification
Scene Recognition
Object Detection
Semantic labeling
Multi-view Object Detection
Fine-grained Visual Recognition
Pedestrian Detection
Video-based
Image Deblurring
Image Captioning
Resource link collection
Aaron Hertzmann (Adobe Research)
Yashar Ganjali, Aaron Hertzmann (University of Toronto)
Simon Peyton Jones (Microsoft Research)
Tao Xie (UIUC) and Yuan Xie (UCSB)
Writing
William T. Freeman (MIT)
Simon Peyton Jones (Microsoft Research)
SIGGRAPH ASIA 2011 Course
Aaron Hertzmann (Adobe Research)
Jim Kajiya (Microsoft Research)
Martin Martin Hering Hering--Bertram (Hochschule Bremen University of Applied Sciences)
Takeo Igarashi (The University of Tokyo)
Derek Hoiem (UIUC)
Wojciech Jarosz (Dartmouth College)
Presentation
David Fleet (University of Toronto) and Aaron Hertzmann (Adobe Research)
Research
Yi Ma (UIUC)
Thomas Funkhouser (Cornell University)
David Chapman (MIT)
Ming-Hsuan Yang (UC Merced)
Jia-Bin Huang (UIUC)
Time Management
Blogs
Full tutorial of computer vision and machine learning basics with OpenCV and Keras in Python.
Links
A curated list of awesome Deep Learning tutorials, projects and communities.
A curated list of awesome Machine Learning frameworks, libraries and software.