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Computer Vision

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Awesome Lists(54 items)

A

Awesome 3D Machine Learning

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Awesome Action Recognition

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Awesome Adversarial Deep Learning

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Awesome Adversarial Machine Learning

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Awesome Anomaly Detection

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Awesome Dataset Tools

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Awesome Deblurring

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Awesome Deep HDR

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Awesome Deep Learning

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Awesome Deep Learning for Tracking and Detection

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Awesome Deep Learning for Video Analysis

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Awesome Deep Vision

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Awesome Document Understanding

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Awesome Domain Adaptation

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Awesome Embodied Vision

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Awesome Explainable AI

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Awesome Face

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Awesome Face Recognition

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Awesome Fairness in AI

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Awesome GAN applications

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Awesome Generative Modeling

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Awesome Graphics

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Awesome Human Pose Estimation

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Awesome Human Pose Estimation

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Awesome Image Classification

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Awesome Image Distortion Correction

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Awesome Image Inpainting

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Awesome Image-to-Image Translation

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Awesome ImageHarmonization

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Awesome Images

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Awesome Implicit Neural Representations

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Awesome Learning with Label Noise

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Awesome Machine Learning

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Awesome Machine Learning in Biomedical(Healthca...

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Awesome Machine Learning Interpretability

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Awesome Makeup Transfer

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Awesome medical imaging

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Awesome Mobile Machine Learning

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Awesome Neural Radiance Fields

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Awesome Neural Rendering

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Awesome Neuron Segmentation in EM Images

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Awesome Object Detection

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Awesome Production Machine Learning

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Awesome Public Datasets

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Awesome Robotics

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Awesome Robotics Datasets

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Awesome Scene Understanding

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Awesome Video Generation

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Awesome Video Text Retrieval

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Awesome Vision + Language

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Awesome Visual Transformer

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Awsome Deep Geometry Learning

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Awsome Delineation

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Awsome GAN Training

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Books(25 items)

B

Bayesian Reasoning and Machine Learning

David Barber, Cambridge University Press, 2012

Books
C

Computer Vision

Linda G. Shapiro 2001

Books
C

Computer Vision for Visual Effects

Richard J. Radke, 2012

Books
C

Computer Vision, From 3D Reconstruction to Reco...

Silvio Savarese 2018

Books
C

Computer Vision: A Modern Approach (2nd edition)

David Forsyth and Jean Ponce 2011

Books
C

Computer Vision: Models, Learning, and Inference

Simon J. D. Prince 2012

Books
C

Computer Vision: Theory and Application

Rick Szeliski 2010

Books
G

Gaussian processes for machine learning

Carl Edward Rasmussen and Christopher K. I. Williams 2005

Books
H

High dynamic range imaging: acquisition, displa...

Reinhard, E., Heidrich, W., Debevec, P., Pattanaik, S., Ward, G., Myszkowski, K 2010

Books
I

Image Processing and Analysis

Stan Birchfield 2018

Books
L

Learning From Data

Yaser S. Abu-Mostafa, Malik Magdon-Ismail and Hsuan-Tien Lin 2012

Books
L

Learning OpenCV: Computer Vision with the OpenC...

Gary Bradski and Adrian Kaehler

Books
L

Linear Algebra and Its Applications

Gilbert Strang 1995

Books
M

Machine Learning

Tom M. Mitchell 1997

Books
M

Multiple View Geometry in Computer Vision

Richard Hartley and Andrew Zisserman 2004

Books
N

Neural Networks and Deep Learning

Michael Nielsen 2014

Books
N

Neural Networks for Pattern Recognition

Christopher M. Bishop 1995

Books
N

Numerical Algorithms: Methods for Computer Visi...

Justin Solomon 2015

Books
O

OpenCV Essentials

Oscar Deniz Suarez, Mª del Milagro Fernandez Carrobles, Noelia Vallez Enano, Gloria Bueno Garcia, Ismael Serrano Gracia

Books
P

Pattern Classification

Peter E. Hart, David G. Stork, and Richard O. Duda 2000

Books
P

Pattern Recognition and Machine Learning

Christopher M. Bishop 2007

Books
P

Practical Python and OpenCV

Adrian Rosebrock

Books
P

Probabilistic Graphical Models: Principles and ...

Daphne Koller and Nir Friedman 2009

Books
V

Vision Science: Photons to Phenomenology

Stephen E. Palmer 1999

Books
V

Visual Object Recognition synthesis lecture

Kristen Grauman and Bastian Leibe 2011

Books

Courses(49 items)

(

(Convolutional) Neural Networks for Visual Reco...

Fei-Fei Li, Andrej Karphaty, Justin Johnson (Stanford University)

Courses
A

Advances in Computer Vision

Antonio Torralba and Bill Freeman (MIT)

Courses
C

Computational Camera and Photography

Ramesh Raskar (MIT Media Lab)

Courses
C

Computational Photography

Alexei A. Efros (CMU)

Courses
C

Computational Photography

Derek Hoiem (UIUC)

Courses
C

Computational Photography

James Hays (Brown University)

Courses
C

Computational Photography

Irfan Essa (Georgia Tech)

Courses
C

Computational Photography

Rob Fergus (NYU)

Courses
C

Computational Photography

Kyros Kutulakos (University of Toronto)

Courses
C

Computer Vision

Steve Seitz (University of Washington)

Courses
C

Computer Vision

Rob Fergus (NYU)

Courses
C

Computer Vision

Derek Hoiem (UIUC)

Courses
C

Computer Vision

Bastian Leibe (RWTH Aachen University)

Courses
C

Computer Vision

Pascal Fua (EPFL):

Courses
C

Computer Vision 1

Carsten Rother (TU Dresden):

Courses
C

Computer Vision 2

Bastian Leibe (RWTH Aachen University)

Courses
C

Computer Vision 2

Carsten Rother (TU Dresden):

Courses
C

Computer Vision for Visual Effects

Rich Radke (Rensselaer Polytechnic Institute)

Courses
C

Computer Vision: Foundations and Applications

Kalanit Grill-Spector and Fei-Fei Li (Stanford University)

Courses
C

Convex Optimization

Stephen Boyd (Stanford University)

Courses
C

Convex Optimization

Ryan Tibshirani (CMU)

Courses
C

Convex Optimization I

Stephen Boyd (Stanford University)

Courses
C

Convex Optimization II

Stephen Boyd (Stanford University)

Courses
C

Convolutional Neural Networks for Visual Recogn...

Fei-Fei Li and Andrej Karpathy (Stanford University)

Courses
C

Course on Information Theory, Pattern Recogniti...

David MacKay (University of Cambridge)

Courses
C

Courses in Graphics

Stanford University

Courses
D

Digital & Computational Photography

Fredo Durand (MIT)

Courses
E

EENG 512 / CSCI 512 - Computer Vision

William Hoff (Colorado School of Mines)

Courses
F

Fall 2016

Visual Recognition , - Kristen Grauman (UT Austin)

Courses
H

High-Level Vision: Behaviors, Neurons and Compu...

Fei-Fei Li (Stanford University)

Courses
I

Image Manipulation and Computational Photography

Alexei A. Efros (UC Berkeley)

Courses
I

Intro to Machine Learning

Sebastian Thrun (Stanford University)

Courses
I

Introduction to Image Processing

Rich Radke (Rensselaer Polytechnic Institute)

Courses
I

Introduction to Visual Computing

Kyros Kutulakos (University of Toronto)

Courses
L

Language and Vision

Tamara Berg (UNC Chapel Hill)

Courses
L

Learning from Data

Yaser S. Abu-Mostafa (Caltech)

Courses
M

Machine Learning

Andrew Ng (Stanford University)

Courses
M

Machine Learning

Andrew Zisserman (University of Oxford)

Courses
M

Machine Learning

Charles Isbell, Michael Littman (Georgia Tech)

Courses
M

Machine Learning for Computer Vision

Rudolph Triebel (TU Munich)

Courses
M

Methods for Applied Statistics: Unsupervised Le...

Lester Mackey (Stanford)

Courses
M

Multiple View Geometry

Daniel Cremers (TU Munich):

Courses
O

Optimization at MIT

(MIT)

Courses
P

Practical Machine Learning

Michael Jordan (UC Berkeley)

Courses
S

Spring 2016

Visual Recognition , - Kristen Grauman (UT Austin)

Courses
S

Statistical Learning

Trevor Hastie and Rob Tibshirani (Stanford University)

Courses
S

Statistical Learning

Genevera Allen (Rice University)

Courses
S

Statistical Learning Theory and Applications

Tomaso Poggio, Lorenzo Rosasco, Carlo Ciliberto, Charlie Frogner, Georgios Evangelopoulos, Ben Deen (MIT)

Courses
V

Visual Object and Activity Recognition

Alexei A. Efros and Trevor Darrell (UC Berkeley)

Courses

Datasets(66 items)

3

3D Object Dataset

Datasets
A

Are we there yet?

Which paper provides the best results on standard dataset X?

Datasets
B

Barcelona Dataset

Datasets
C

Caltech Pedestrian Detection Benchmark

Datasets
C

Caltech-UCSD Birds 200

Datasets
C

CAM2

Datasets
C

CamVid

Datasets
C

ChangeDetection.net

Datasets
C

ChangeDetection.net

Datasets
C

Computer Vision Dataset on the web

Datasets
C

ComputerVisionOnline Datasets

Datasets
C

CV datasets

Datasets
C

CV Datasets on the web

CVPapers

Datasets
C

CVOnline Dataset

Datasets
D

DAVIS: Densely Annotated VIdeo Segmentation

Datasets
E

EPFL Car Dataset

Datasets
E

ETHZ Pedestrian Detection

Datasets
F

Fine-grained Classification Challenge

Datasets
F

Flickr 30K

Datasets
F

Flickr 8K

Datasets
F

Flickr Material Database

Datasets
G

Ground Truth Stixel Dataset

Datasets
G

Ground-truth dataset and baseline evaluations f...

Datasets
H

HCI Challenge

Datasets
H

HOLLYWOOD2 Dataset

Datasets
I

ImageNet Large Scale Visual Recognition Challenge

Datasets
I

ImageNet Object Detection Challenge

Datasets
I

Intrinsic Image Evaluation on Synthetic Complex...

Datasets
I

Intrinsic Images in the Wild

Datasets
K

KTTI Dection Dataset

Datasets
L

Labeled and Annotated Sequences for Integral Ev...

Datasets
L

Levin dataset

Datasets
L

LIBELAS: Library for Efficient Large-scale Ster...

Datasets
M

Materials in Context Dataset

Datasets
M

Microsoft COCO

Datasets
M

Microsoft COCO

Datasets
M

Middlebury Optical Flow Evaluation

Datasets
M

Middlebury Stereo Vision

Datasets
M

MPI-Sintel Optical Flow Dataset and Evaluation

Datasets
M

Multi-View Stereo Reconstruction

Datasets
N

NYU Car Dataset

Datasets
O

OpenSurface

Datasets
P

PASCAL 3D+

Datasets
P

PASS: An An ImageNet replacement for self-super...

Datasets
P

Place Dataset

Datasets
P

Princeton Tracking Benchmark

Datasets
S

SegTrack v2

Datasets
S

SIFT Flow Dataset

Datasets
S

Single-Image Super-Resolution: A Benchmark

Datasets
S

Stanford background dataset

Datasets
S

SUN 3D Dataset

Datasets
S

SUN Database

Datasets
S

Sun dataset

Datasets
T

The KITTI Vision Benchmark Suite

Datasets
T

The KITTI Vision Benchmark Suite

Datasets
T

The PASCAL Visual Object Classes

Datasets
T

The PASCAL Visual Object Classes

Datasets
T

Tracking Manipulation Tasks (TMT)

Datasets
U

UCF Sports Action Data Set

Datasets
V

VIRAT

Datasets
V

visionbib

Datasets
V

Visual Tracker Benchmark

Datasets
V

Visual Tracker Benchmark v1.1

Datasets
V

VisualData

Datasets
V

VOT Challenge

Datasets
Y

Yet Another Computer Vision Index To Datasets

Datasets

Resources for students(32 items)

A

Advice for Graduate Students

Aaron Hertzmann (Adobe Research)

Resources for students
C

Common mistakes in technical writing

Wojciech Jarosz (Dartmouth College)

Resources for students
D

Designing conference posters

Colin Purrington

Resources for students
F

Five Principles for Choosing Research Problems ...

Thomas Funkhouser (Cornell University)

Resources for students
G

Giving a Research Talk

Frédo Durand (MIT)

Resources for students
G

Good Writing

Marc H. Raibert (Boston Dynamics, Inc.)

Resources for students
G

Graduate Skills Seminars

Yashar Ganjali, Aaron Hertzmann (University of Toronto)

Resources for students
H

How to Come Up with Research Ideas in Computer ...

Jia-Bin Huang (UIUC)

Resources for students
H

How to do research

William T. Freeman (MIT)

Resources for students
H

How To Do Research In the MIT AI Lab

David Chapman (MIT)

Resources for students
H

How to Get Your SIGGRAPH Paper Rejected

Jim Kajiya (Microsoft Research)

Resources for students
H

How to give a good talk

David Fleet (University of Toronto) and Aaron Hertzmann (Adobe Research)

Resources for students
H

How to have a paper get into SIGGRAPH?

Takeo Igarashi (The University of Tokyo)

Resources for students
H

How to Read Academic Papers

Jia-Bin Huang (UIUC)

Resources for students
H

How to Write a Bad Article

Frédo Durand (MIT)

Resources for students
H

How to Write a Computer Vision Paper

Derek Hoiem (UIUC)

Resources for students
H

How to write a good CVPR submission

William T. Freeman (MIT)

Resources for students
H

How to Write a Great Paper

Martin Martin Hering Hering--Bertram (Hochschule Bremen University of Applied Sciences)

Resources for students
H

How to write a great research paper

Simon Peyton Jones (Microsoft Research)

Resources for students
H

How to Write a Paper for SIGGRAPH

Jim Blinn

Resources for students
H

How to write a SIGGRAPH paper

SIGGRAPH ASIA 2011 Course

Resources for students
N

Notes on writing

Frédo Durand (MIT)

Resources for students
R

Recent Advances in Computer Vision

Ming-Hsuan Yang (UC Merced)

Resources for students
R

Research Skills

Simon Peyton Jones (Microsoft Research)

Resources for students
R

Resource collection

Tao Xie (UIUC) and Yuan Xie (UCSB)

Resources for students
R

Resources for students

Frédo Durand (MIT)

Resources for students
S

Seven Warning Signs of Bogus Science

Robert L. Park

Resources for students
T

Time Management

Randy Pausch (CMU)

Resources for students
W

Warning Signs of Bogus Progress in Research in ...

Yi Ma (UIUC)

Resources for students
W

Write Good Papers

Frédo Durand (MIT)

Resources for students
W

Writing Research Papers

Aaron Hertzmann (Adobe Research)

Resources for students
Y

You and Your Research

Richard Hamming

Resources for students

Software(203 items)

A

A+: Adjusted Anchored Neighborhood Regression

Software
A

Accurate Scale Estimation for Robust Visual Tra...

Software
A

Adaptive Manifold

Software
A

AKAZE

Software
A

Alpha Matting Evaluation

Software
A

ANN: A Library for Approximate Nearest Neighbor...

Software
A

Annotorious

Software
A

Awesome 3D reconstruction list

Software
A

Awesome Deep Vision

Software
A

Awesome Machine Learning

Software
B

BING: Objectness Estimation

Software
B

Blind Deblurring Using Internal Patch Recurrence

Software
B

Blind Deconvolution Using a Normalized Sparsity...

Software
B

Blur kernel estimation using the radon transform

Software
B

Blur-kernel estimation from spectral irregulari...

Software
B

Bob: a free signal processing and machine learn...

Software
B

BRISK

Software
B

Bundler SFM

Software
C

C++/MatLab Optical Flow by C. Liu (based on Bro...

Software
C

Camera Calibration Toolbox for Matlab

Software
C

Camera calibration With OpenCV

Software
C

ccv: A Modern Computer Vision Library

Software
C

Ceres Solver

Nonlinear least-square problem and unconstrained optimization solver

Software
C

CF2: Hierarchical Convolutional Features for Vi...

Software
C

Closed-form image matting

Software
C

Clustering Views for Multi-view Stereo

Software
C

CMT: Clustering of Static-Adaptive Corresponden...

Software
C

CMU Computer Vision Page

Software
C

Coarse2Fine Optical Flow

Ce Liu (MIT)

Software
C

Coherency Sensitive Hashing

Software
C

Comma Coloring

Software
C

Computer Vision Algorithm Implementations

CVPapers

Software
C

Computer Vision Resources

Jia-Bin Huang (UIUC)

Software
C

Contour Detection and Image Segmentation

Software
C

Contour Relaxed Superpixels

Software
C

CurveLab

Software
D

DBoW2: binary bag-of-words loop detection system

Software
D

Deep Convolutional Neural Network for Image Dec...

Software
D

Deformable Patches

Software
D

Discriminatively trained deformable part models

Software
D

Domain Transform

Software
D

DVO: dense visual odometry

Software
E

Edge Boxes

Software
E

Edge-based Blur Kernel Estimation Using Patch P...

Software
E

Efficient hierarchical graph-based video segmen...

Software
E

Efficient marginal likelihood optimization in b...

Software
E

Enhanced adaptive coupled-layer LGTracker++

Software
E

Entropy Rate Superpixel

Software
E

Extended Lucas-Kanade Tracking

Software
F

FabMap: appearance-based loop closure system

also available in OpenCV2.4.11

Software
F

Fast Bilateral Filter

Software
F

Fast Edge Detection Using Structured Forests

Software
F

Fast k nearest neighbor search using GPU

Software
F

Fast motion deblurring

Software
F

Fast Removal of Non-uniform Camera Shake

Software
F

FLANN - Fast Library for Approximate Nearest Ne...

Software
F

Floating Scale Surface Reconstruction

Software
F

FOVIS: RGB-D visual odometry

Software
F

FREAK

Software
F

From Learning Models of Natural Image Patches t...

Software
G

G2O: General framework for graph optomization

Software
G

Generalized PatchMatch

Software
G

Geodesic Graph Cut

Software
G

Geodesic Segmentation

Software
G

Geometric Context

Derek Hoiem (CMU)

Software
G

Geometric Reasoning

David C. Lee (CMU)

Software
G

GIMP Resynthesizer

Software
G

Grab Cut

Software
G

Graph-based Segmentation

Software
G

Ground Truth Stixel Dataset

Software
G

gtmaker

Software
G

GTSAM

Factor graph based lease-square optimization solver

Software
G

GTSAM: General smoothing and mapping library fo...

Georgia Institute of Technology

Software
G

Guided image filtering

Software
H

Handling Outliers in Non-blind Image Deconvolution

Software
H

HCI Challenge

Software
H

HDR_Toolbox

Software
H

High-quality motion deblurring from a single image

Software
H

Histograms of Sparse Codes for Object Detection

Software
H

Hyper-Laplacian Priors

Software
I

Image Deblurring using Inertial Measurement Sen...

Software
I

ImageMelding

Software
I

ImageUtilities

Software
I

Improving Image Matting using Comprehensive Sam...

Software
I

InfiniTAM: Implementation of multi-platform lar...

Software
I

INRIA Object Detection and Localization Toolkit

Software
I

Intrinsic Images by Clustering

Software
K

Kanade-Lucas-Tomasi Feature Tracker

Software
K

Kernelized Correlation Filters

Software
K

KFusion: Implementation of KinectFusion

Software
K

kinfu_remake: Lightweight, reworked and optimiz...

Software
K

Kitti Odometry: benchmark for outdoor visual od...

Software
L

L0 Gradient Optimization

Software
L

LabelME

Software
L

Large-Scale Texturing of 3D Reconstructions

Software
L

Lazy Snapping

Software
L

Learning-based Matting

Software
L

LIBELAS: Library for Efficient Large-scale Ster...

Software
L

LIBSVM -- A Library for Support Vector Machines

Software
L

LIBVISO2: C++ Library for Visual Odometry 2

Software
L

List of Semantic Segmentation algorithms

Software
L

Local Binary Patterns

Software
L

Locality Sensitive Histograms

Software
L

LSD-SLAM

Software
L

LVR-KinFu: kinfu_remake based Large Scale Kinec...

Software
M

Markov Random Fields for Super-Resolution

Software
M

Matlab Computer Vision System Toolbox

Software
M

MATLAB Functions for Multiple View Geometry

Software
M

Mean Shift Segmentation

Software
M

mexopencv

Software
M

Middlebury Optical Flow Evaluation

Software
M

Middlebury Stereo Vision

Software
M

MinimalSolvers

Minimal problems solver

Software
M

Modular Tracking Framework

Software
M

MPI-Sintel Optical Flow Dataset and Evaluation

Software
M

Multi-frame image super-resolution

Software
M

Multi-View Environment

Software
M

Multiple Camera Calibration Toolbox

Software
M

Multiple Experts using Entropy Minimization

Software
M

Multiscale Combinatorial Grouping

Software
N

Neighbor embedding

Software
N

Neural Deconvolution

Software
N

NeuralTalk

Software
N

NLopt

Nonlinear least-square problem and unconstrained optimization solver

Software
N

Non-uniform Deblurring for Shaken Images

Software
N

Normalized Cut

Software
O

O(1) Bilateral Filter

Software
O

Object segmentation in video

Software
O

Online-boosting Tracking

Software
O

Open CV

Software
O

Open source Python module for computer vision

Software
O

OpenGM

Factor graph based discrete optimization and inference solver

Software
O

OpenGV

geometric computer vision algorithms

Software
O

openMVG: open Multiple View Geometry

Multiple View Geometry; Structure from Motion library & softwares

Software
O

openSLAM

Software
O

ORB-SLAM

Software
P

Parallel Robust Optical Flow by Sánchez Pérez e...

Software
P

Patch-based Multi-view Stereo V2

Software
P

Patch-wise Sparse Recovery

Software
P

PatchMatch

Software
P

PCL: Point Cloud Library

Software
P

Peter Kovesi's Matlab Functions for Computer Vi...

Software
P

Piotr's Computer Vision Matlab Toolbox

Software
P

PlanarStructureCompletion

Software
P

PMBP: PatchMatch Belief Propagation

Software
P

Pointwise Mutual Information

Software
P

Power Watershed

Software
P

Priority BP

Software
P

PTAM: Parallel tracking and mapping

Software
Q

QuickShift

Software
R

R-CNN: Regions with Convolutional Neural Networ...

Software
R

Random Walker

Software
R

RatSLAM

Software
R

Recovering Intrinsic Images with a global Spars...

Software
R

Recovering Spatial Layout

Varsha Hedau (UIUC)

Software
R

Recursive Bilateral Filtering

Software
R

ReInspect

Software
R

Relative Total Variation

Software
R

Removing Camera Shake From A Single Photograph

Software
R

RetargetMe

Software
R

RGBD2Full3D

Ruiqi Guo (UIUC)

Software
R

Rolling Guidance Filter

Software
S

Secrets of Optical Flow Estimation and Their Pr...

Software
S

SEEDS

Software
S

SEEDS Revised

Software
S

Segmentation by Transduction

Software
S

SIFT

Software
S

SIFT++

Software
S

SimpleCV

Software
S

Single Image Deblurring Using Motion Density Fu...

Software
S

Single-Image Super Resolution via a Statistical...

Software
S

SLAMBench: Multiple-implementation of KinectFusion

Software
S

SLIC Super-pixel

Software
S

Source Code Collection for Reproducible Research

Xin Li (West Virginia University)

Software
S

Sparse Coding for Super-Resolution

Software
S

Sparse regression and natural image prior

Software
S

Spatially variant non-blind deconvolution

Software
S

Spatio-Temporal Context Learning

Software
S

Spectral Matting

Software
S

SPP-Net

Software
S

SRCNN

Software
S

Streaming hierarchical video segmentation

Software
S

Structured Edge Detection

Software
S

SURF

Software
S

SVO: Semi-direct visual odometry

Software
T

TGPR

Software
T

The KITTI Vision Benchmark Suite

Software
T

The KITTI Vision Benchmark Suite

Software
T

The Steerable Pyramid

Software
T

TLD: Tracking - Learning - Detection

Software
T

Transformed Self-Exemplars

Software
T

TreeCANN

Software
T

TurboPixels

Software
T

Two-Phase Kernel Estimation for Robust Motion D...

Software
U

Unnatural L0 Sparse Representation for Natural ...

Software
V

Video Segmentation with Superpixels

Software
V

Visual SFM

Software
V

Visual Tracker Benchmark

Software
V

Visual Tracking Challenge

Software
V

VLFeat

Software
V

VLFeat

Software
V

VOC-DPM

Software
V

VoxelHashing: Large-scale KinectFusion

Software

Tutorials and talks(59 items)

3

3D Computer Vision: Past, Present, and Future

Steve Seitz (University of Washington) 2011

Tutorials and talks
A

A Gentle Tutorial of the EM Algorithm

Jeff A. Bilmes (UC Berkeley) 1998

Tutorials and talks
A

A Tour of Modern "Image Processing"

Peyman Milanfar (UC Santa Cruz/Google) 2010

Tutorials and talks
A

A Trillion Photos

Steve Seitz (University of Washington) 2013

Tutorials and talks
A

A tutorial on Deep Learning

Geoffrey E. Hinton (University of Toronto)

Tutorials and talks
A

Applications to Machine Vision

Andrew Blake (Microsoft Research) 2008

Tutorials and talks
B

Bayesian or Frequentist, Which Are You?

Michael I. Jordan (UC Berkeley)

Tutorials and talks
B

Beyond stochastic gradient descent for large-sc...

Francis Bach (INRIA)

Tutorials and talks
C

Computational Photography

William T. Freeman (MIT) 2012

Tutorials and talks
C

Computer Vision Talks

Lectures, keynotes, panel discussions on computer vision

Tutorials and talks
C

Continuous Optimization in Computer Vision

Andrew Fitzgibbon (Microsoft Research)

Tutorials and talks
C

Convex Optimization

Lieven Vandenberghe (University of California, Los Angeles)

Tutorials and talks
C

CVPR 2012

Jun 2012

Tutorials and talks
C

CVPR 2013

Jun 2013

Tutorials and talks
C

CVPR 2014

Jun 2014

Tutorials and talks
C

CVPR 2015

Jun 2015

Tutorials and talks
D

Deep Learning

Ruslan Salakhutdinov (University of Toronto)

Tutorials and talks
D

Deep Learning for Computer Vision

Rob Fergus (NYU/Facebook Research)

Tutorials and talks
D

Deep Learning Session 1

Yoshua Bengio (Universtiy of Montreal)

Tutorials and talks
D

Deep Learning Session 2

Yoshua Bengio (University of Montreal)

Tutorials and talks
D

Deep Learning Session 3

Yoshua Bengio (University of Montreal)

Tutorials and talks
E

ECCV 2012

Oct 2012

Tutorials and talks
E

ECCV 2014

Sep 2014

Tutorials and talks
G

Generative Models for Visual Objects and Object...

Fei-Fei Li (Stanford University)

Tutorials and talks
G

Graduate Summer School 2012: Deep Learning, Fea...

IPAM, 2012

Tutorials and talks
G

Graduate Summer School 2013: Computer Vision

IPAM, 2013

Tutorials and talks
G

Graphical Models

Zoubin Ghahramani (University of Cambridge) 2009

Tutorials and talks
G

Graphical Models and Applications

Yair Weiss (The Hebrew University of Jerusalem) 2009

Tutorials and talks
G

Graphical Models for Computer Vision

Pedro Felzenszwalb (Brown University) 2012

Tutorials and talks
H

High-dimensional learning with deep network con...

Stéphane Mallat (Ecole Normale Superieure)

Tutorials and talks
I

ICCV 2013

Dec 2013

Tutorials and talks
I

ICML 2012

Jun 2012

Tutorials and talks
I

ICML 2013

Jul 2013

Tutorials and talks
I

ImageNet Classification with Deep Convolutional...

Alex Krizhevsky (University of Toronto)

Tutorials and talks
I

Introduction To Bayesian Inference

Christopher Bishop (Microsoft Research) 2009

Tutorials and talks
L

Learning and Inference in Low-Level Vision

Yair Weiss (The Hebrew University of Jerusalem) 2009

Tutorials and talks
L

Learning in Computer Vision

Simon Lucey (CMU) 2008

Tutorials and talks
M

Machine Learning Summer School

Reykjavik, Iceland 2014

Tutorials and talks
M

Machine Learning, Probability and Graphical Models

Sam Roweis (NYU) 2006

Tutorials and talks
O

Object Recognition

Larry Zitnick (Microsoft Research)

Tutorials and talks
O

Old and New algorithm for Blind Deconvolution

Yair Weiss (The Hebrew University of Jerusalem) 2011

Tutorials and talks
O

Optimization Algorithms in Machine Learning

Stephen J. Wright (University of Wisconsin-Madison)

Tutorials and talks
O

Overview of Computer Vision and Visual Effects

Rich Radke (Rensselaer Polytechnic Institute) 2014

Tutorials and talks
P

Photographing Events over Time

William T. Freeman (MIT) 2011

Tutorials and talks
P

Planet-Scale Visual Understanding

Noah Snavely (Cornell University) 2014

Tutorials and talks
R

Reconstructing the World from Photos on the Int...

Steve Seitz (University of Washington) 2013

Tutorials and talks
R

Reflections on Image-Based Modeling and Rendering

Richard Szeliski (Microsoft Research) 2013

Tutorials and talks
R

Revealing the Invisible

Frédo Durand (MIT) 2012

Tutorials and talks
S

Scaling up Deep Learning

Yoshua Bengio (University of Montreal)

Tutorials and talks
S

Should I do a PhD in Computer Vision?

Fatih Porikli (Australian National University)

Tutorials and talks
S

Support Vector Machines

Chih-Jen Lin (National Taiwan University) 2006

Tutorials and talks
T

The Distributed Camera

Noah Snavely (Cornell University) 2011

Tutorials and talks
T

The Future of Image Search

Jitendra Malik (UC Berkeley) 2008

Tutorials and talks
T

The Three R's of Computer Vision

Jitendra Malik (UC Berkeley) 2013

Tutorials and talks
T

The Unreasonable Effectivness Of Deep Learning

Yann LeCun (NYU/Facebook Research) 2014

Tutorials and talks
T

Topics in image and video processing

Andrew Blake (Microsoft Research) 2007

Tutorials and talks
V

Variational Methods for Computer Vision

Daniel Cremers (Technische Universität München) (lecture 18 missing from playlist)

Tutorials and talks
W

Where machine vision needs help from machine le...

William T. Freeman (MIT) 2011

Tutorials and talks
W

Workshop on Big Data and Statistical Machine Le...

Tutorials and talks