Top 50 Awesome List

jbhuang0604/awesome-computer-vision

Computer Science  27 days ago  15.1k
A curated list of awesome computer vision resources
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Sep 28th

Feb 28th

Pre-trained Computer Vision Models

  • List of Computer Vision modelsstars17 These models are trained on custom objects
  • Jan 12th

    Jan 11th

    Awesome Lists

  • Awesome Anomaly Detectionstars1.7k
  • Awesome Deep Learning for Video Analysisstars508
  • Awesome Roboticsstars2.5k
  • Awesome Visual Transformerstars1.9k
  • Awesome Embodied Visionstars148
  • Awesome Implicit Neural Representationsstars1.1k
  • Awesome Machine Learningstars51.7k
  • Awesome Deep Visionstars9.7k
  • Awesome Domain Adaptationstars3.2k
  • Awesome Object Detectionstars6.6k
  • Awesome 3D Machine Learningstars7.2k
  • Awesome Action Recognitionstars3.2k
  • Awesome Scene Understandingstars364
  • Awesome Adversarial Machine Learningstars1.6k
  • Awesome Adversarial Deep Learningstars219
  • Awesome Facestars778
  • Awesome Face Recognitionstars3.1k
  • Awesome Human Pose Estimationstars983
  • Awesome medical imagingstars123
  • Awesome Imagesstars2.2k
  • Awesome Graphicsstars854
  • Awesome Neural Radiance Fieldsstars1.4k
  • Awesome Neural Renderingstars862
  • Awesome Public Datasetsstars46.2k
  • Awesome Dataset Toolsstars574
  • Awesome Robotics Datasetsstars155
  • Awesome Mobile Machine Learningstars1.2k
  • Awesome Explainable AIstars429
  • Awesome Fairness in AIstars178
  • Awesome Machine Learning Interpretabilitystars2.3k
  • Awesome Production Machine Learningstars10.2k
  • Awesome Video Text Retrievalstars181
  • Awesome Image-to-Image Translationstars570
  • Awesome Image Inpaintingstars842
  • Awesome Deep HDRstars217
  • Awesome Video Generationstars45
  • Awesome GAN applicationsstars3.8k
  • Awesome Generative Modelingstars130
  • Awesome Image Classificationstars2k
  • Awesome Deep Learningstars17.8k
  • Awesome Machine Learning in Biomedical(Healthcare) Imagingstars26
  • Awesome Deep Learning for Tracking and Detectionstars1.9k
  • Awesome Human Pose Estimationstars983
  • Awesome Vision + Languagestars622
  • Dec 30th, 2020

    Books

    Computer Vision

  • Computer Vision, From 3D Reconstruction to Recognition - Silvio Savarese 2018
  • Dec 12th, 2020

    Books

    Computer Vision

  • Image Processing and Analysis - Stan Birchfield 2018
  • Mar 20th, 2019

    Jan 17th, 2018

    Courses

    Machine Learning and Statistical Learning

  • Machine Learning for Computer Vision - Rudolph Triebel (TU Munich)
  • Jan 16th, 2018

    Blogs

  • Computer Vision Basics with Python Keras and OpenCVstars406 - Jason Chin (University of Western Ontario)
  • Nov 24th, 2017

    Datasets

    External Dataset Link Collection

  • VisualData
  • May 25th, 2017

    Datasets

    Video Object Segmentation
  • DAVIS: Densely Annotated VIdeo Segmentation
  • SegTrack v2
  • May 9th, 2017

    Courses

    Computer Vision

  • Computer Vision Pascal Fua (EPFL):
  • Computer Vision 1 Carsten Rother (TU Dresden):
  • Computer Vision 2 Carsten Rother (TU Dresden):
  • Multiple View Geometry Daniel Cremers (TU Munich):
  • Mar 7th, 2017

    Courses

    Machine Learning and Statistical Learning

  • (Convolutional) Neural Networks for Visual Recognition - Fei-Fei Li, Andrej Karphaty, Justin Johnson (Stanford University)
  • Nov 1st, 2016

    Courses

    Computer Vision

  • Visual Recognition Spring 2016, Fall 2016 - Kristen Grauman (UT Austin)
  • Computer Vision - Bastian Leibe (RWTH Aachen University)
  • Computer Vision 2 - Bastian Leibe (RWTH Aachen University)
  • Oct 26th, 2016

    Courses

    Machine Learning and Statistical Learning

  • Intro to Machine Learning - Sebastian Thrun (Stanford University)
  • Machine Learning - Charles Isbell, Michael Littman (Georgia Tech)
  • Courses

    Computational Photography

  • Computational Photography - Irfan Essa (Georgia Tech)
  • Courses

    Computer Vision

  • Advances in Computer Vision - Antonio Torralba and Bill Freeman (MIT)
  • Links

  • Sep 11th, 2016

    Aug 21st, 2016

    Jun 10th, 2016

    Software

    Visual Tracking

  • Modular Tracking Framework
  • May 24th, 2016

    Software

    Semantic Segmentation

  • List of Semantic Segmentation algorithms
  • Mar 18th, 2016

    Datasets

    Visual Tracking

  • Tracking Manipulation Tasks (TMT)
  • Jan 20th, 2016

    Courses

    Computational Photography

  • Computer Vision for Visual Effects - Rich Radke (Rensselaer Polytechnic Institute)
  • Introduction to Image Processing - Rich Radke (Rensselaer Polytechnic Institute)
  • Courses

    Machine Learning and Statistical Learning

  • Machine Learning - Andrew Ng (Stanford University)
  • Tutorials and talks

    Object Recognition

  • Object Recognition - Larry Zitnick (Microsoft Research)
  • Tutorials and talks

    Machine Learning

  • A Gentle Tutorial of the EM Algorithm - Jeff A. Bilmes (UC Berkeley) 1998
  • Software

    Multiple-view Computer Vision

  • Peter Kovesi's Matlab Functions for Computer Vision and Image Analysis
  • MinimalSolvers - Minimal problems solver
  • Multi-View Environment
  • Software

    Contour Detection and Image Segmentation

  • SLIC Super-pixel
  • Contour Relaxed Superpixels
  • Software

    Loop Closure:
  • FabMap: appearance-based loop closure system - also available in OpenCV2.4.11
  • Links

  • awesome-deep-learningstars17.8k
  • Oct 2nd, 2015

    Courses

    Machine Learning and Statistical Learning

  • Course on Information Theory, Pattern Recognition, and Neural Networks - David MacKay (University of Cambridge)
  • Software

    External Resource Links

  • CMU Computer Vision Page
  • Software

    Feature Detection and Extraction

  • SIFT
    • David G. Lowe, "Distinctive image features from scale-invariant keypoints," International Journal of Computer Vision, 60, 2 (2004), pp. 91-110.
  • Software

    Image Completion
  • ImageMelding
  • Software

    Image Retargeting
  • RetargetMe
  • Software

    Contour Detection and Image Segmentation

  • SEEDS Revisedstars49
  • Software

    Tracking/Odometry:
  • LIBVISO2: C++ Library for Visual Odometry 2
  • KFusion: Implementation of KinectFusionstars185
  • Software

    Localization & Mapping:
  • LSD-SLAMstars2.2k
  • Software

    Image Captioning

  • NeuralTalk -
  • Blogs

  • Computer Vision Talks - Eugene Khvedchenya
  • Sep 2nd, 2015

    Software

    Object Detection

  • ReInspect
  • Aug 9th, 2015

    Software

    General Purpose Computer Vision Library

  • mexopencv
  • Software

    Machine Learning

  • LIBSVM -- A Library for Support Vector Machines
  • Tutorials and talks

    Recent Conference Talks

  • ICML 2013 - Jul 2013
  • ICML 2012 - Jun 2012
  • Books

    Computer Vision

  • High dynamic range imaging: acquisition, display, and image-based lighting - Reinhard, E., Heidrich, W., Debevec, P., Pattanaik, S., Ward, G., Myszkowski, K 2010
  • Books

    Machine Learning

  • Gaussian processes for machine learning - Carl Edward Rasmussen and Christopher K. I. Williams 2005
  • Software

    High Dynamic Range Imaging

  • HDR_Toolboxstars263
  • Aug 4th, 2015

    Books

    Computer Vision

  • Computer Vision for Visual Effects - Richard J. Radke, 2012
  • Tutorials and talks

    Computational Photography

  • Overview of Computer Vision and Visual Effects - Rich Radke (Rensselaer Polytechnic Institute) 2014
  • Jul 24th, 2015

    Blogs

  • AI Shack - Utkarsh Sinha
  • Jun 21st, 2015

    Software

    Deep Learning

  • Awesome Deep Visionstars9.7k
  • Datasets

    Material Recognition

  • Materials in Context Dataset
  • Datasets

    Pedestrian Detection
  • ETHZ Pedestrian Detection
  • Datasets

    Video-based
  • UCF Sports Action Data Set
  • Datasets

    Image Deblurring
  • Levin dataset
  • Jun 1st, 2015

    Resources for students

    Resource link collection

  • Resource collection - Tao Xie (UIUC) and Yuan Xie (UCSB)
  • Resources for students

    Writing

  • Common mistakes in technical writing - Wojciech Jarosz (Dartmouth College)
  • Songs

  • Machine Learning A Cappella - Overfitting Thriller
  • May 31st, 2015

    Courses

    Computer Vision

  • EENG 512 / CSCI 512 - Computer Vision - William Hoff (Colorado School of Mines)
  • May 30th, 2015

    Blogs

  • Learn OpenCV - Satya Mallick
  • Tombone's Computer Vision Blog - Tomasz Malisiewicz
  • Computer vision for dummies - Vincent Spruyt
  • Andrej Karpathy blog - Andrej Karpathy
  • May 21st, 2015

    May 14th, 2015

    Tutorials and talks

    Computer Vision

  • Computer Vision Talks - Lectures, keynotes, panel discussions on computer vision
  • Apr 19th, 2015

    Software

    Optimization

  • OpenGM - Factor graph based discrete optimization and inference solver
  • NLopt- Nonlinear least-square problem and unconstrained optimization solver
  • Software

    General Purpose Computer Vision Library

  • PCL: Point Cloud Library
  • ImageUtilities
  • Software

    Tracking/Odometry:
  • VoxelHashing: Large-scale KinectFusionstars499
  • SLAMBench: Multiple-implementation of KinectFusion
  • SVO: Semi-direct visual odometrystars1.7k
  • DVO: dense visual odometrystars544
  • FOVIS: RGB-D visual odometry
  • Software

    Multiple-view Computer Vision

  • openMVG: open Multiple View Geometry - Multiple View Geometry; Structure from Motion library & softwares
  • Patch-based Multi-view Stereo V2
  • Clustering Views for Multi-view Stereo
  • Software

    Localization & Mapping:
  • ORB-SLAMstars1.2k
  • Apr 18th, 2015

    Software

    Optimization

  • Ceres Solver - Nonlinear least-square problem and unconstrained optimization solver
  • GTSAM - Factor graph based lease-square optimization solver
  • Software

    Loop Closure:
  • DBoW2: binary bag-of-words loop detection system
  • Software

    SLAM community:
  • Kitti Odometry: benchmark for outdoor visual odometry (codes may be available)
  • Software

    Tracking/Odometry:
  • PTAM: Parallel tracking and mapping
  • InfiniTAM: Implementation of multi-platform large-scale depth tracking and fusion
  • Software

    Graph Optimization:
  • GTSAM: General smoothing and mapping library for Robotics and SFM -- Georgia Institute of Technology
  • G2O: General framework for graph optomizationstars2k
  • Tutorials and talks

    Deep Learning

  • Graduate Summer School 2012: Deep Learning, Feature Learning - IPAM, 2012
  • Workshop on Big Data and Statistical Machine Learning
  • Machine Learning Summer School - Reykjavik, Iceland 2014
  • Apr 5th, 2015

    Tutorials and talks

    Recent Conference Talks

  • CVPR 2015 - Jun 2015
  • Mar 11th, 2015

    Tutorials and talks

    Computational Photography

  • Revealing the Invisible - Frédo Durand (MIT) 2012
  • Mar 2nd, 2015

    Software

    Super-resolution
  • Transformed Self-Exemplars
    • Jia-Bin Huang, Abhishek Singh, and Narendra Ahuja, Single Image Super-Resolution using Transformed Self-Exemplars, IEEE Conference on Computer Vision and Pattern Recognition, 2015
  • Feb 27th, 2015

    Software

    Feature Detection and Extraction

  • Local Binary Patternsstars92
  • Feb 26th, 2015

    Software

    Intrinsic Images

  • Recovering Intrinsic Images with a global Sparsity Prior on Reflectance
  • Intrinsic Images by Clustering
  • Software

    Contour Detection and Image Segmentation

  • SEEDS
  • Software

    Video Segmentation

  • Streaming hierarchical video segmentation
  • Feb 23rd, 2015

    Books

    OpenCV Programming

  • OpenCV Essentials - Oscar Deniz Suarez, Mª del Milagro Fernandez Carrobles, Noelia Vallez Enano, Gloria Bueno Garcia, Ismael Serrano Gracia
  • Feb 22nd, 2015

    Software

    Feature Detection and Extraction

  • SIFT++
  • Feb 20th, 2015

    Courses

    Machine Learning and Statistical Learning

  • Machine Learning - Andrew Zisserman (University of Oxford)
  • Books

    OpenCV Programming

  • Practical Python and OpenCV - Adrian Rosebrock
  • Feb 19th, 2015

    Courses

    Machine Learning and Statistical Learning

  • Methods for Applied Statistics: Unsupervised Learning - Lester Mackey (Stanford)
  • Datasets

    Intrinsic Images

  • Intrinsic Image Evaluation on Synthetic Complex Scenes
  • Books

    Machine Learning

  • Bayesian Reasoning and Machine Learning - David Barber, Cambridge University Press, 2012
  • Jan 23rd, 2015

    Tutorials and talks

    Recent Conference Talks

  • ECCV 2014 - Sep 2014
  • CVPR 2014 - Jun 2014
  • ICCV 2013 - Dec 2013
  • CVPR 2013 - Jun 2013
  • ECCV 2012 - Oct 2012
  • CVPR 2012 - Jun 2012
  • Jan 22nd, 2015

    Tutorials and talks

    Optimization

  • Variational Methods for Computer Vision - Daniel Cremers (Technische Universität München) (lecture 18 missing from playlist)
  • Jan 19th, 2015

    Software

    Contour Detection and Image Segmentation

  • Entropy Rate Superpixel
  • Software

    Interactive Image Segmentation

  • Random Walker
  • Geodesic Segmentation
  • Lazy Snapping
  • Power Watershed
  • Geodesic Graph Cut
  • Segmentation by Transduction
  • Software

    External Resource Links

  • Source Code Collection for Reproducible Research - Xin Li (West Virginia University)
  • Computer Vision Resources - Jia-Bin Huang (UIUC)
  • Computer Vision Algorithm Implementations - CVPapers
  • Software

    General Purpose Computer Vision Library

  • Matlab Computer Vision System Toolbox
  • VLFeat
  • Open CV
  • Software

    Multiple-view Computer Vision

  • MATLAB Functions for Multiple View Geometry
  • Books

    Fundamentals

  • Linear Algebra and Its Applications - Gilbert Strang 1995
  • Software

    Feature Detection and Extraction

  • AKAZE
    • Pablo F. Alcantarilla, Adrien Bartoli and Andrew J. Davison, "KAZE Features", ECCV 2012
  • BRISK
    • Stefan Leutenegger, Margarita Chli and Roland Siegwart, "BRISK: Binary Robust Invariant Scalable Keypoints", ICCV 2011
  • SURF
    • Herbert Bay, Andreas Ess, Tinne Tuytelaars, Luc Van Gool, "SURF: Speeded Up Robust Features", Computer Vision and Image Understanding (CVIU), Vol. 110, No. 3, pp. 346--359, 2008
  • FREAK
    • A. Alahi, R. Ortiz, and P. Vandergheynst, "FREAK: Fast Retina Keypoint", CVPR 2012
  • Links

  • Cat Paper Collection
  • The Computer Vision Industry - David Lowe
  • Datasets

    Image Captioning

  • Flickr 8K
  • Flickr 30K
  • Microsoft COCO
  • Resources for students

    Research

  • 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)
  • How to do research - William T. Freeman (MIT)
  • You and Your Research - Richard Hamming
  • Warning Signs of Bogus Progress in Research in an Age of Rich Computation and Information - Yi Ma (UIUC)
  • 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)
  • Papers

    Survey Papers

  • Visionbib Survey Paper List
  • Foundations and Trends® in Computer Graphics and Vision
  • Computer Vision: A Reference Guide
  • Tutorials and talks

    Optimization

  • Beyond stochastic gradient descent for large-scale machine learning - Francis Bach (INRIA)
  • Continuous Optimization in Computer Vision - Andrew Fitzgibbon (Microsoft Research)
  • Tutorials and talks

    Deep Learning

  • High-dimensional learning with deep network contractions - Stéphane Mallat (Ecole Normale Superieure)
  • Deep Learning for Computer Vision - Rob Fergus (NYU/Facebook Research)
  • Software

    Stereo Vision
  • Ground Truth Stixel Dataset
  • Datasets

    Stereo Vision
  • Middlebury Stereo Vision
  • The KITTI Vision Benchmark Suite
  • LIBELAS: Library for Efficient Large-scale Stereo Matching
  • Ground Truth Stixel Dataset
  • Datasets

    Optical Flow
  • Middlebury Optical Flow Evaluation
  • MPI-Sintel Optical Flow Dataset and Evaluation
  • The KITTI Vision Benchmark Suite
  • HCI Challenge
  • Datasets

    Image Super-resolutions
  • Single-Image Super-Resolution: A Benchmark
  • Software

    Image Deblurring
  • From Learning Models of Natural Image Patches to Whole Image Restoration
  • Spatially variant non-blind deconvolution
  • Handling Outliers in Non-blind Image Deconvolution
  • Hyper-Laplacian Priors
  • Deep Convolutional Neural Network for Image Deconvolution
  • Neural Deconvolution
  • Datasets

    Image Deblurring
  • Sun dataset
  • Datasets

    Multi-view Object Detection
  • 3D Object Dataset
  • EPFL Car Dataset
  • KTTI Dection Dataset
  • SUN 3D Dataset
  • PASCAL 3D+
  • NYU Car Dataset
  • Datasets

    Pedestrian Detection
  • Caltech Pedestrian Detection Benchmark
  • Datasets

    Video-based
  • HOLLYWOOD2 Dataset
  • Datasets

    Intrinsic Images

  • Ground-truth dataset and baseline evaluations for intrinsic image algorithms
  • Intrinsic Images in the Wild
  • Datasets

    Material Recognition

  • OpenSurface
  • Flickr Material Database
  • Datasets

    Multi-view Reconsturction

  • Multi-View Stereo Reconstruction
  • Datasets

    Change detection

  • ChangeDetection.net
  • Datasets

    Image Classification
  • The PASCAL Visual Object Classes
  • ImageNet Large Scale Visual Recognition Challenge
  • Datasets

    Scene Recognition
  • SUN Database
  • Place Dataset
  • Datasets

    Object Detection
  • The PASCAL Visual Object Classes
  • ImageNet Object Detection Challenge
  • Microsoft COCO
  • Datasets

    Semantic labeling
  • Stanford background dataset
  • CamVid
  • Barcelona Dataset
  • SIFT Flow Dataset
  • Datasets

    Fine-grained Visual Recognition
  • Fine-grained Classification Challenge
  • Caltech-UCSD Birds 200
  • Software

    Nearest Neighbor Field Estimation
  • TreeCANN
  • PatchMatch
  • Generalized PatchMatch
  • Coherency Sensitive Hashing
  • PMBP: PatchMatch Belief Propagationstars24
  • Software

    Image Pyramid
  • The Steerable Pyramid
  • CurveLab
  • Software

    SLAM community:
  • openSLAM
  • Software

    Localization & Mapping:
  • RatSLAM
  • Papers

    Conference papers on the web

  • Calendar of Computer Image Analysis, Computer Vision Conferences - (USC)
  • Tutorials and talks

    Machine Learning

  • Bayesian or Frequentist, Which Are You? - Michael I. Jordan (UC Berkeley)
  • Software

    Object Detection

  • Histograms of Sparse Codes for Object Detection
  • Tutorials and talks

    Computer Vision

  • The Future of Image Search - Jitendra Malik (UC Berkeley) 2008
  • Should I do a PhD in Computer Vision? - Fatih Porikli (Australian National University)
  • Tutorials and talks

    3D Computer Vision

  • Reconstructing the World from Photos on the Internet - Steve Seitz (University of Washington) 2013
  • Software

    General purpose nearest neighbor search
  • ANN: A Library for Approximate Nearest Neighbor Searching
  • FLANN - Fast Library for Approximate Nearest Neighbors
  • Fast k nearest neighbor search using GPU
  • Software

    Alpha Matting
  • Closed-form image matting
  • Spectral Matting
  • Learning-based Matting
  • Improving Image Matting using Comprehensive Sampling Sets
  • Software

    Optical Flow
  • Coarse2Fine Optical Flow - Ce Liu (MIT)
  • Software

    Super-resolution
  • Sparse Coding for Super-Resolution
    • R. Zeyde, M. Elad, and M. Protter On Single Image Scale-Up using Sparse-Representations, Curves & Surfaces, Avignon-France, June 24-30, 2010 (appears also in Lecture-Notes-on-Computer-Science - LNCS).
  • Datasets

    External Dataset Link Collection

  • visionbib
  • CV datasets
  • CV Datasets on the web - CVPapers
  • Are we there yet? - Which paper provides the best results on standard dataset X?
  • Computer Vision Dataset on the web
  • Yet Another Computer Vision Index To Datasets
  • ComputerVisionOnline Datasets
  • CVOnline Dataset
  • Datasets

    Visual Tracking

  • Visual Tracker Benchmark
  • Visual Tracker Benchmark v1.1
  • VOT Challenge
  • Princeton Tracking Benchmark
  • Datasets

    Visual Surveillance

  • VIRAT
  • CAM2
  • Software

    Single-view Spatial Understanding

  • Geometric Context - Derek Hoiem (CMU)
  • Recovering Spatial Layout - Varsha Hedau (UIUC)
  • Geometric Reasoning - David C. Lee (CMU)
  • RGBD2Full3Dstars23 - Ruiqi Guo (UIUC)
  • Software

    Video Segmentation

  • Video Segmentation with Superpixels
  • Efficient hierarchical graph-based video segmentation
  • Object segmentation in video
  • Resources for students

    Resource link collection

  • 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)
  • Resources for students

    Writing

  • 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)
  • Resources for students

    Presentation

  • 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
  • Resources for students

    Time Management

  • Time Management - Randy Pausch (CMU)
  • Jan 18th, 2015

    Software

    Feature Detection and Extraction

  • VLFeat
  • Software

    Image Completion
  • Priority BP
  • PlanarStructureCompletion
  • Software

    Alpha Matting
  • Alpha Matting Evaluation
  • Software

    Edge-preserving image processing
  • Fast Bilateral Filter
  • O(1) Bilateral Filter
  • Recursive Bilateral Filtering
  • Rolling Guidance Filter
  • Relative Total Variation
  • L0 Gradient Optimization
  • Domain Transform
  • Adaptive Manifold
  • Guided image filtering
  • Software

    Contour Detection and Image Segmentation

  • Mean Shift Segmentation
  • Graph-based Segmentation
  • Normalized Cut
  • Contour Detection and Image Segmentation
  • Structured Edge Detection
  • Pointwise Mutual Information
  • QuickShift
  • TurboPixels
  • Books

    Computer Vision

  • Vision Science: Photons to Phenomenology - Stephen E. Palmer 1999
  • Visual Object Recognition synthesis lecture - Kristen Grauman and Bastian Leibe 2011
  • Courses

    Machine Learning and Statistical Learning

  • 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)
  • Courses

    Optimization

  • Optimization at MIT - (MIT)
  • Convex Optimization - Ryan Tibshirani (CMU)
  • Papers

    Conference papers on the web

  • CVPapers - Computer vision papers on the web
  • SIGGRAPH Paper on the web - Graphics papers on the web
  • NIPS Proceedings - NIPS papers on the web
  • Tutorials and talks

    Computer Vision

  • The Three R's of Computer Vision - Jitendra Malik (UC Berkeley) 2013
  • Applications to Machine Vision - Andrew Blake (Microsoft Research) 2008
  • Tutorials and talks

    3D Computer Vision

  • 3D Computer Vision: Past, Present, and Future - Steve Seitz (University of Washington) 2011
  • Tutorials and talks

    Internet Vision

  • 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
  • Tutorials and talks

    Computational Photography

  • 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
  • Tutorials and talks

    Learning and Vision

  • 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
  • Tutorials and talks

    Object Recognition

  • Generative Models for Visual Objects and Object Recognition via Bayesian Inference - Fei-Fei Li (Stanford University)
  • Tutorials and talks

    Graphical Models

  • 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
  • Tutorials and talks

    Machine Learning

  • Introduction To Bayesian Inference - Christopher Bishop (Microsoft Research) 2009
  • Support Vector Machines - Chih-Jen Lin (National Taiwan University) 2006
  • Tutorials and talks

    Optimization

  • Optimization Algorithms in Machine Learning - Stephen J. Wright (University of Wisconsin-Madison)
  • Convex Optimization - Lieven Vandenberghe (University of California, Los Angeles)
  • Tutorials and talks

    Deep Learning

  • 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
  • Software

    Super-resolution
  • Patch-wise Sparse Recovery
    • Jianchao Yang, John Wright, Thomas Huang, and Yi Ma. Image super-resolution via sparse representation. IEEE Transactions on Image Processing (TIP), vol. 19, issue 11, 2010.
  • Neighbor embedding
    • H. Chang, D.Y. Yeung, Y. Xiong. Super-resolution through neighbor embedding. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), vol.1, pp.275-282, Washington, DC, USA, 27 June - 2 July 2004.
  • Deformable Patches
    • Yu Zhu, Yanning Zhang and Alan Yuille, Single Image Super-resolution using Deformable Patches, CVPR 2014
  • SRCNN
    • Chao Dong, Chen Change Loy, Kaiming He, Xiaoou Tang, Learning a Deep Convolutional Network for Image Super-Resolution, in ECCV 2014
  • Jan 17th, 2015

    Software

    Stereo Vision
  • Middlebury Stereo Vision
  • The KITTI Vision Benchmark Suite
  • LIBELAS: Library for Efficient Large-scale Stereo Matching
  • Software

    Optical Flow
  • Middlebury Optical Flow Evaluation
  • MPI-Sintel Optical Flow Dataset and Evaluation
  • The KITTI Vision Benchmark Suite
  • HCI Challenge
  • Secrets of Optical Flow Estimation and Their Principles
  • Software

    Super-resolution
  • Multi-frame image super-resolution
    • Pickup, L. C. Machine Learning in Multi-frame Image Super-resolution, PhD thesis 2008
  • Markov Random Fields for Super-Resolution
    • W. T Freeman and C. Liu. Markov Random Fields for Super-resolution and Texture Synthesis. In A. Blake, P. Kohli, and C. Rother, eds., Advances in Markov Random Fields for Vision and Image Processing, Chapter 10. MIT Press, 2011
  • Sparse regression and natural image prior
    • K. I. Kim and Y. Kwon, "Single-image super-resolution using sparse regression and natural image prior", IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 32, no. 6, pp. 1127-1133, 2010.
  • Single-Image Super Resolution via a Statistical Model
    • T. Peleg and M. Elad, A Statistical Prediction Model Based on Sparse Representations for Single Image Super-Resolution, IEEE Transactions on Image Processing, Vol. 23, No. 6, Pages 2569-2582, June 2014
  • A+: Adjusted Anchored Neighborhood Regression
    • R. Timofte, V. De Smet, and L. Van Gool. A+: Adjusted Anchored Neighborhood Regression for Fast Super-Resolution, ACCV 2014
  • Software

    Image Completion
  • GIMP Resynthesizer
  • Software

    General Purpose Computer Vision Library

  • Piotr's Computer Vision Matlab Toolbox
  • Software

    Object Detection

  • INRIA Object Detection and Localization Toolkit
  • Discriminatively trained deformable part models
  • VOC-DPMstars566
  • R-CNN: Regions with Convolutional Neural Network Featuresstars2.2k
  • SPP-Netstars358
  • Jan 16th, 2015

    Books

    Machine Learning

  • Neural Networks and Deep Learning - Michael Nielsen 2014
  • 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
  • Learning From Data- Yaser S. Abu-Mostafa, Malik Magdon-Ismail and Hsuan-Tien Lin 2012
  • Papers

    Conference papers on the web

  • Computer Vision Foundation open access
  • Annotated Computer Vision Bibliography - Keith Price (USC)
  • Software

    Multiple-view Computer Vision

  • Visual SFM
  • Bundler SFM
  • Floating Scale Surface Reconstruction
  • OpenGV - geometric computer vision algorithms
  • Software

    Camera calibration

  • Camera Calibration Toolbox for Matlab
  • Camera calibration With OpenCV
  • Multiple Camera Calibration Toolbox
  • Software

    Visual Tracking

  • Visual Tracker Benchmark
  • Visual Tracking Challenge
  • Kanade-Lucas-Tomasi Feature Tracker
  • Books

    OpenCV Programming

  • Learning OpenCV: Computer Vision with the OpenCV Library - Gary Bradski and Adrian Kaehler
  • Software

    General Purpose Computer Vision Library

  • SimpleCV
  • Courses

    Computer Vision

  • Visual Object and Activity Recognition - Alexei A. Efros and Trevor Darrell (UC Berkeley)
  • Computer Vision - Steve Seitz (University of Washington)
  • 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)
  • Courses

    Computational Photography

  • 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)
  • 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)
  • Courses

    Optimization

  • Convex Optimization I - Stephen Boyd (Stanford University)
  • Convex Optimization II - Stephen Boyd (Stanford University)
  • Convex Optimization - Stephen Boyd (Stanford University)
  • Songs

  • The Fundamental Matrix Song
  • The RANSAC Song
  • Books

    Computer Vision

  • 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
  • Last Checked At: 2021-10-25T04:05:57.773Z
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