计算机视觉、机器学习相关领域论文和源代码大集合

古城微笑少年丶 2022-06-15 10:27 225阅读 0赞

**[计算机视觉][Link 1]、[机器学习][Link 2]相关领域论文和源代码大集合**

**http://blog.csdn.net/tiandijun/article/details/22321609**

**一、特征提取Feature Extraction：**

· SIFT \[1\] \[[Demo program][]\]\[[SIFT Library][]\] \[[VLFeat][]\]

· PCA-SIFT \[2\] \[[Project][]\]

· Affine-SIFT \[3\] \[[Project][Project 1]\]

· SURF \[4\] \[[OpenSURF][]\] \[[Matlab Wrapper][]\]

· Affine Covariant Features \[5\] \[[Oxford project][]\]

· MSER \[6\] \[[Oxford project][]\] \[[VLFeat][]\]

· Geometric Blur \[7\] \[[Code][]\]

· Local Self-Similarity Descriptor \[8\] \[[Oxford implementation][]\]

· Global and Efficient Self-Similarity \[9\] \[[Code][Code 1]\]

· Histogram of Oriented Graidents \[10\] \[[INRIA Object Localization Toolkit][]\] \[[OLT toolkit for Windows][]\]

· GIST \[11\] \[[Project][Project 2]\]

· Shape Context \[12\] \[[Project][Project 3]\]

· Color Descriptor \[13\] \[[Project][Project 4]\]

· Pyramids of Histograms of Oriented Gradients \[[Code][Code 2]\]

· Space-Time Interest Points (STIP) \[14\]\[[Project][Project 5]\] \[[Code][Code 3]\]

· Boundary Preserving Dense Local Regions \[15\]\[[Project][Project 6]\]

· Weighted Histogram\[[Code][Code 4]\]

· Histogram-based Interest Points Detectors\[[Paper][]\]\[[Code][Code 5]\]

· An [OpenCV][] \- C++ implementation of Local Self Similarity Descriptors \[[Project][Project 7]\]

· Fast Sparse Representation with Prototypes\[[Project][Project 8]\]

· Corner Detection \[[Project][Project 9]\]

· AGAST Corner Detector: faster than FAST and even FAST-ER\[[Project][Project 10]\]

· Real-time Facial Feature Detection using Conditional Regression Forests\[[Project][Project 11]\]

· Global and Efficient Self-Similarity for Object Classification and Detection\[[code][]\]

· WαSH: Weighted α-Shapes for Local Feature Detection\[[Project][Project 12]\]

· HOG\[[Project][Project 13]\]

· Online Selection of Discriminative Tracking Features\[[Project][Project 14]\]

**二、图像分割Image Segmentation：**

· Normalized Cut \[1\] \[[Matlab code][]\]

· Gerg Mori’ Superpixel code \[2\] \[[Matlab code][Matlab code 1]\]

· Efficient Graph-based Image Segmentation \[3\] \[[C++ code][C_ code]\] \[[Matlab wrapper][]\]

· Mean-Shift Image Segmentation \[4\] \[[EDISON C++ code][EDISON C_ code]\] \[[Matlab wrapper][Matlab wrapper 1]\]

· OWT-UCM Hierarchical Segmentation \[5\] \[[Resources][]\]

· Turbepixels \[6\] \[[Matlab code 32bit][]\] \[[Matlab code 64bit][]\] \[[Updated code][]\]

· Quick-Shift \[7\] \[[VLFeat][VLFeat 1]\]

· SLIC Superpixels \[8\] \[[Project][Project 15]\]

· Segmentation by Minimum Code Length \[9\] \[[Project][Project 16]\]

· Biased Normalized Cut \[10\] \[[Project][Project 17]\]

· Segmentation Tree \[11-12\] \[[Project][Project 18]\]

· Entropy Rate Superpixel Segmentation \[13\] \[[Code][Code 6]\]

· Fast Approximate Energy Minimization via Graph Cuts\[[Paper][Paper 1]\]\[[Code][Code 7]\]

· Efﬁcient Planar Graph Cuts with Applications in Computer Vision\[[Paper][Paper 2]\]\[[Code][Code 8]\]

· Isoperimetric Graph Partitioning for Image Segmentation\[[Paper][Paper 3]\]\[[Code][Code 9]\]

· Random Walks for Image Segmentation\[[Paper][Paper 4]\]\[[Code][Code 10]\]

· Blossom V: A new implementation of a minimum cost perfect matching algorithm\[[Code][Code 11]\]

· An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Computer Vision\[[Paper][Paper 5]\]\[[Code][Code 12]\]

· Geodesic Star Convexity for Interactive Image Segmentation\[[Project][Project 19]\]

· Contour Detection and Image Segmentation Resources\[[Project][Resources]\]\[[Code][Code 13]\]

· Biased Normalized Cuts\[[Project][Project 20]\]

· Max-flow/min-cut\[[Project][Project 21]\]

· Chan-Vese Segmentation using Level Set\[[Project][Project 22]\]

· A Toolbox of Level Set Methods\[[Project][Project 23]\]

· Re-initialization Free Level Set Evolution via Reaction Diffusion\[[Project][Project 24]\]

· Improved C-V active contour model\[[Paper][Paper 6]\]\[[Code][Code 14]\]

· A Variational Multiphase Level Set Approach to Simultaneous Segmentation and Bias Correction\[[Paper][Paper 7]\]\[[Code][Code 15]\]

· Level Set Method Research by Chunming Li\[[Project][Project 25]\]

· ClassCut for Unsupervised Class Segmentation\[[cod][]e\]

· SEEDS: Superpixels Extracted via Energy-Driven Sampling[\[Project][Project 26]\]\[[other][]\]

**三、目标检测Object Detection：**

· A simple object detector with boosting \[[Project][Project 27]\]

· INRIA Object Detection and Localization Toolkit \[1\] \[[Project][Project 28]\]

· Discriminatively Trained Deformable Part Models \[2\] \[[Project][Project 29]\]

· Cascade Object Detection with Deformable Part Models \[3\] \[[Project][Project 30]\]

· Poselet \[4\] \[[Project][Project 31]\]

· Implicit Shape Model \[5\] \[[Project][Project 32]\]

· Viola and Jones’s Face Detection \[6\] \[[Project][Project 33]\]

· Bayesian Modelling of Dyanmic Scenes for Object Detection\[[Paper][Paper 8]\]\[[Code][Code 16]\]

· Hand detection using multiple proposals\[[Project][Project 34]\]

· Color Constancy, Intrinsic Images, and Shape Estimation\[[Paper][Paper 9]\]\[[Code][Code 17]\]

· Discriminatively trained deformable part models\[[Project][Project 35]\]

· Gradient Response Maps for Real-Time Detection of Texture-Less Objects: LineMOD \[[Project][Project 36]\]

· Image Processing On Line\[[Project][Project 37]\]

· Robust Optical Flow Estimation\[[Project][Project 38]\]

· Where's Waldo: Matching People in Images of Crowds\[[Project][Project 39]\]

· Scalable Multi-class Object Detection\[[Project][Project 40]\]

· Class-Specific Hough Forests for Object Detection\[[Project][Project 41]\]

· Deformed Lattice Detection In Real-World Images\[[Project][Project 42]\]

· Discriminatively trained deformable part models\[[Project][Project 35]\]

**四、显著性检测Saliency Detection：**

· Itti, Koch, and Niebur’ saliency detection \[1\] \[[Matlab code][Matlab code 2]\]

· Frequency-tuned salient region detection \[2\] \[[Project][Project 43]\]

· Saliency detection using maximum symmetric surround \[3\] \[[Project][Project 44]\]

· Attention via Information Maximization \[4\] \[[Matlab code][Matlab code 3]\]

· Context-aware saliency detection \[5\] \[[Matlab code][Matlab code 4]\]

· Graph-based visual saliency \[6\] \[[Matlab code][Matlab code 5]\]

· Saliency detection: A spectral residual approach. \[7\] \[[Matlab code][Matlab code 6]\]

· Segmenting salient objects from images and videos. \[8\] \[[Matlab code][Matlab code 7]\]

· Saliency Using Natural statistics. \[9\] \[[Matlab code][Matlab code 8]\]

· Discriminant Saliency for Visual Recognition from Cluttered Scenes. \[10\] \[[Code][Code 18]\]

· Learning to Predict Where Humans Look \[11\] \[[Project][Project 45]\]

· Global Contrast based Salient Region Detection \[12\] \[[Project][Project 46]\]

· Bayesian Saliency via Low and Mid Level Cues\[[Project][Project 47]\]

· Top-Down Visual Saliency via Joint CRF and Dictionary Learning\[[Paper][Paper 10]\]\[[Code][Code 19]\]

· Saliency Detection: A Spectral Residual Approach\[[Code][Code 20]\]

**五、图像分类、聚类Image Classification, Clustering**

· Pyramid Match \[1\] \[[Project][Project 48]\]

· Spatial Pyramid Matching \[2\] \[[Code][Code 21]\]

· Locality-constrained Linear Coding \[3\] \[[Project][Project 49]\] \[[Matlab code][Matlab code 9]\]

· Sparse Coding \[4\] \[[Project][Project 50]\] \[[Matlab code][Matlab code 10]\]

· Texture Classification \[5\] \[[Project][Project 51]\]

· Multiple Kernels for Image Classification \[6\] \[[Project][Code]\]

· Feature Combination \[7\] \[[Project][Project 52]\]

· SuperParsing \[[Code][Code 22]\]

· Large Scale Correlation Clustering Optimization\[[Matlab code][Matlab code 11]\]

· Detecting and Sketching the Common\[[Project][Project 53]\]

· Self-Tuning Spectral Clustering\[[Project][Project 54]\]\[[Code][Code 23]\]

· User Assisted Separation of Reflections from a Single Image Using a Sparsity Prior\[[Paper][Paper 11]\]\[[Code][Code 24]\]

· Filters for Texture Classification\[[Project][Project 55]\]

· Multiple Kernel Learning for Image Classification\[[Project][Code]\]

· SLIC Superpixels\[[Project][Project 56]\]

**六、抠图Image Matting**

· A Closed Form Solution to Natural Image Matting \[[Code][Code 25]\]

· Spectral Matting \[[Project][Project 57]\]

· Learning-based Matting \[[Code][Code 26]\]

**七、目标跟踪Object Tracking：**

· A Forest of Sensors - Tracking Adaptive Background Mixture Models \[[Project][Project 58]\]

· Object Tracking via Partial Least Squares Analysis\[[Paper][Paper 12]\]\[[Code][Code 27]\]

· Robust Object Tracking with Online Multiple Instance Learning\[[Paper][Paper 13]\]\[[Code][Code 28]\]

· Online Visual Tracking with Histograms and Articulating Blocks\[[Project][Project 59]\]

· Incremental Learning for Robust Visual Tracking\[[Project][Project 60]\]

· Real-time Compressive Tracking\[[Project][Project 61]\]

· Robust Object Tracking via Sparsity-based Collaborative Model\[[Project][Project 62]\]

· Visual Tracking via Adaptive Structural Local Sparse Appearance Model\[[Project][Project 63]\]

· Online Discriminative Object Tracking with Local Sparse Representation\[[Paper][Paper 14]\]\[[Code][Code 29]\]

· Superpixel Tracking\[[Project][Project 64]\]

· Learning Hierarchical Image Representation with Sparsity, Saliency and Locality\[[Paper][Paper 15]\]\[[Code][Code 30]\]

· Online Multiple Support Instance Tracking \[[Paper][Paper 16]\]\[[Code][Code 31]\]

· Visual Tracking with Online Multiple Instance Learning\[[Project][Code 28]\]

· Object detection and recognition\[[Project][Project 65]\]

· Compressive Sensing Resources\[[Project][Project 66]\]

· Robust Real-Time Visual Tracking using Pixel-Wise Posteriors\[[Project][Project 67]\]

· Tracking-Learning-Detection\[[Project][Project 68]\]\[[OpenTLD/C++ Code][OpenTLD_C_ Code]\]

· the HandVu：vision-based hand gesture interface\[[Project][Project 69]\]

· Learning Probabilistic Non-Linear Latent Variable Models for Tracking Complex Activities\[[Project][Project 70]\]

**八、Kinect：**

· Kinect toolbox\[[Project][Project 71]\]

· OpenNI\[[Project][Project 72]\]

· zouxy09 CSDN Blog\[[Resource][]\]

· FingerTracker 手指跟踪\[[code][code 1]\]

**九、3D相关：**

· 3D Reconstruction of a Moving Object\[[Paper][Paper 17]\] \[[Code][Code 32]\]

· Shape From Shading Using Linear Approximation\[[Code][Code 33]\]

· Combining Shape from Shading and Stereo Depth Maps\[[Project][Project 73]\]\[[Code][Code 34]\]

· Shape from Shading: A Survey\[[Paper][Paper 18]\]\[[Code][Code 35]\]

· A Spatio-Temporal Descriptor based on 3D Gradients (HOG3D)\[[Project][Project 74]\]\[[Code][Code 36]\]

· Multi-camera Scene Reconstruction via Graph Cuts\[[Paper][Paper 19]\]\[[Code][Code 37]\]

· A Fast Marching Formulation of Perspective Shape from Shading under Frontal Illumination\[[Paper][Paper 20]\]\[[Code][Code 38]\]

· Reconstruction:3D Shape, Illumination, Shading, Reflectance, Texture\[[Project][Project 75]\]

· Monocular Tracking of 3D Human Motion with a Coordinated Mixture of Factor Analyzers\[[Code][Code 39]\]

· Learning 3-D Scene Structure from a Single Still Image\[[Project][Project 76]\]

**十、机器学习[算法][Link 3]：**

· Matlab class for computing Approximate Nearest Nieghbor (ANN) \[[Matlab class][] providing interface to[ANN library][]\]

· Random Sampling\[[code][code 2]\]

· Probabilistic Latent Semantic Analysis (pLSA)\[[Code][Code 40]\]

· FASTANN and FASTCLUSTER for approximate k-means (AKM)\[[Project][Project 77]\]

· Fast Intersection / Additive Kernel SVMs\[[Project][Project 78]\]

· SVM\[[Code][Code 41]\]

· Ensemble learning\[[Project][Project 65]\]

· Deep Learning\[[Net][]\]

· Deep Learning Methods for Vision\[[Project][Project 79]\]

· Neural Network for Recognition of Handwritten Digits\[[Project][Project 80]\]

· Training a deep autoencoder or a classifier on MNIST digits\[[Project][Project 81]\]

· THE MNIST DATABASE of handwritten digits\[[Project][Project 82]\]

· Ersatz：deep neural networks in the cloud\[[Project][Project 83]\]

· Deep Learning \[[Project][Project 84]\]

· sparseLM : Sparse Levenberg-Marquardt nonlinear least squares in C/C++\[[Project][Project 85]\]

· Weka 3: Data Mining Software in [Java][]\[[Project][Project 86]\]

· Invited talk "A Tutorial on Deep Learning" by Dr. Kai Yu (余凯)\[[Video][]\]

· CNN - Convolutional neural network class\[[Matlab Tool][]\]

· Yann LeCun's Publications\[[Wedsite][]\]

· LeNet-5, convolutional neural networks\[[Project][Project 87]\]

· Training a deep autoencoder or a classifier on MNIST digits\[[Project][Project 81]\]

· Deep Learning 大牛Geoffrey E. Hinton's HomePage\[[Website][]\]

· Multiple Instance Logistic Discriminant-based Metric Learning (MildML) and Logistic Discriminant-based Metric Learning (LDML)\[[Code][Code 42]\]

· Sparse coding simulation software\[[Project][Project 88]\]

· Visual Recognition and Machine Learning Summer School\[[Software][]\]

**十一、目标、行为识别Object, Action Recognition：**

· Action Recognition by Dense Trajectories\[[Project][Project 89]\]\[[Code][Code 43]\]

· Action Recognition Using a Distributed Representation of Pose and Appearance\[[Project][Project 90]\]

· Recognition Using Regions\[[Paper][Paper 21]\]\[[Code][Code 44]\]

· 2D Articulated Human Pose Estimation\[[Project][Project 91]\]

· Fast Human Pose Estimation Using Appearance and Motion via Multi-Dimensional Boosting Regression\[[Paper][Paper 22]\]\[[Code][Code 45]\]

· Estimating Human Pose from Occluded Images\[[Paper][Paper 23]\]\[[Code][Code 46]\]

· Quasi-dense wide baseline matching\[[Project][Project 92]\]

· ChaLearn Gesture Challenge: Principal motion: PCA-based reconstruction of motion histograms\[[Project][Project 93]\]

· Real Time Head Pose Estimation with Random Regression Forests\[[Project][Project 94]\]

· 2D Action Recognition Serves 3D Human Pose Estimation\[[Project\]][Project 95]

· A Hough Transform-Based Voting Framework for Action Recognition\[[Project\]][Project 96]

· Motion Interchange Patterns for Action Recognition in Unconstrained Videos\[[Project\]][Project 97]

· 2D articulated human pose estimation software\[[Project][Project 98]\]

· Learning and detecting shape models \[[code][code 3]\]

· Progressive Search Space Reduction for Human Pose Estimation\[[Project][Project 99]\]

· Learning Non-Rigid 3D Shape from 2D Motion\[[Project][Project 100]\]

**十二、图像处理：**

· Distance Transforms of Sampled Functions\[[Project][Project 101]\]

· The Computer Vision Homepage\[[Project][Project 102]\]

· Efficient appearance distances between windows\[[code][code 4]\]

· Image Exploration algorithm\[[code][code 5]\]

· Motion Magnification 运动放大 \[[Project][Project 103]\]

· Bilateral Filtering for Gray and Color Images 双边滤波器 \[[Project][Project 104]\]

· A Fast Approximation of the Bilateral Filter using a Signal Processing Approach \[[Project\]][Project 105]

**十三、一些实用工具：**

· EGT: a Toolbox for Multiple View Geometry and Visual Servoing\[[Project][Project 106]\] \[[Code][Code 47]\]

· a development kit of matlab mex functions for OpenCV library\[[Project][Project 107]\]

· Fast Artificial Neural Network Library\[[Project][Project 108]\]

**十四、人手及指尖检测与识别：**

· finger-detection-and-gesture-recognition \[[Code][Code 48]\]

· Hand and Finger Detection using JavaCV\[[Project][Project 109]\]

· Hand and fingers detection\[[Code][Code 49]\]

**十五、场景解释：**

· Nonparametric Scene Parsing via Label Transfer \[[Project][Project 110]\]

**十六、光流Optical flow：**

· High accuracy optical flow using a theory for warping \[[Project][Project 111]\]

· Dense Trajectories Video Description \[[Project][Project 89]\]

· SIFT Flow: Dense Correspondence across Scenes and its Applications\[[Project][Project 112]\]

· KLT: An Implementation of the Kanade-Lucas-Tomasi Feature Tracker \[[Project][Project 113]\]

· Tracking Cars Using Optical Flow\[[Project][Project 114]\]

· Secrets of optical flow estimation and their principles\[[Project][Project 115]\]

· implmentation of the Black and Anandan dense optical flow method\[[Project][Project 115]\]

· Optical Flow Computation\[[Project][Project 116]\]

· Beyond Pixels: Exploring New Representations and Applications for Motion Analysis\[[Project][Project 117]\]

· A Database and Evaluation Methodology for Optical Flow\[[Project][Project 118]\]

· optical flow relative\[[Project][Project 119]\]

· Robust Optical Flow Estimation \[[Project][Project 38]\]

· optical flow\[[Project][Project 120]\]

**十七、图像检索Image Retrieval：**

· Semi-Supervised Distance Metric Learning for Collaborative Image Retrieval [\[Paper][Paper 24]\]\[[code][code 6]\]

**十八、马尔科夫随机场Markov Random Fields：**

· Markov Random Fields for Super-Resolution [\[][Paper 24][Project][Project 121]\]

· A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors \[[Project][Project 122]\]

**十九、运动检测Motion detection：**

· Moving Object Extraction, Using Models or Analysis of Regions [\[][Paper 24][Project][Project 123]\]

· Background Subtraction: Experiments and Improvements for ViBe \[[Project][Project 124]\]

· A Self-Organizing Approach to Background Subtraction for Visual Surveillance Applications \[[Project][Project 125]\]

· changedetection[.NET][]: A new change detection benchmark dataset\[[Project][Project 126]\]

· ViBe - a powerful technique for background detection and subtraction in video sequences\[[Project][Project 127]\]

· Background Subtraction Program\[[Project][Project 128]\]

· Motion Detection Algorithms\[[Project][Project 129]\]

· Stuttgart Artificial Background Subtraction Dataset\[[Project][Project 130]\]

· Object Detection, Motion Estimation, and Tracking\[[Project][Project 131]\]

Feature Detection and Description

General Libraries:

*  [VLFeat][] – Implementation of various feature descriptors (including SIFT, HOG, and LBP) and covariant feature detectors (including DoG, Hessian, Harris Laplace, Hessian Laplace, Multiscale Hessian, Multiscale Harris). Easy-to-use Matlab interface. See [Modern features: Software][Modern features_ Software] – Slides providing a demonstration of VLFeat and also links to other software. Check also [VLFeat hands-on session training][]
 *  [OpenCV][OpenCV 1] – Various implementations of modern feature detectors and descriptors (SIFT, SURF, FAST, BRIEF, ORB, FREAK, etc.)

Fast Keypoint Detectors for Real-time Applications:

*  [FAST][] – High-speed corner detector implementation for a wide variety of platforms
 *  [AGAST][Project 10] – 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][] – C++ code for a fast and accurate interest point descriptor (not invariant to rotations and scale) (ECCV 2010)
 *  [ORB][] – OpenCV implementation of the Oriented-Brief (ORB) descriptor (invariant to rotations, but not scale)
 *  [BRISK][] – Efficient Binary descriptor invariant to rotations and scale. It includes a Matlab mex interface. (ICCV 2011)
 *  [FREAK][] – Faster than BRISK (invariant to rotations and scale) (CVPR 2012)

SIFT and SURF Implementations:

*  SIFT: [VLFeat][], [OpenCV][OpenCV 2], [Original code][] by David Lowe, [GPU implementation][], [OpenSIFT][]
 *  SURF: [Herbert Bay’s code][Herbert Bay_s code], [OpenCV][OpenCV 2], [GPU-SURF][]

Other Local Feature Detectors and Descriptors:

*  [VGG Affine Covariant features][Oxford project] – Oxford code for various affine covariant feature detectors and descriptors.
 *  [LIOP descriptor][] – Source code for the Local Intensity order Pattern (LIOP) descriptor (ICCV 2011).
 *  [Local Symmetry Features][] – Source code for matching of local symmetry features under large variations in lighting, age, and rendering style (CVPR 2012).

Global Image Descriptors:

*  [GIST][Project 2] – Matlab code for the GIST descriptor
 *  [CENTRIST][] – Global visual descriptor for scene categorization and object detection (PAMI 2011)

Feature Coding and Pooling

*  [VGG Feature Encoding 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][] – Source code for feature pooling based on spatial pyramid matching (widely used for image classification)

Convolutional Nets and Deep Learning

*  [EBLearn][] – C++ Library for Energy-Based Learning. It includes several demos and step-by-step instructions to train classifiers based on convolutional neural networks.
 *  [Torch7][] – Provides a matlab-like environment for state-of-the-art machine learning algorithms, including a fast implementation of convolutional neural networks.
 *  [Deep Learning][] \- Various links for deep learning software.

Part-Based Models

*  [Deformable Part-based Detector][Project 35] – Library provided by the authors of the original paper (state-of-the-art in PASCAL VOC detection task)
 *  [Efficient Deformable Part-Based Detector][] – Branch-and-Bound implementation for a deformable part-based detector.
 *  [Accelerated Deformable Part Model][] – 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][] – Fast approach for deformable object detection (CVPR 2011).
 *  [Poselets][Project 31] – C++ and Matlab versions for object detection based on poselets.
 *  [Part-based Face Detector and Pose Estimation][] – Implementation of a unified approach for face detection, pose estimation, and landmark localization (CVPR 2012).

Attributes and Semantic Features

*  [Relative Attributes][] – Modified implementation of RankSVM to train Relative Attributes (ICCV 2011).
 *  [Object Bank][] – Implementation of object bank semantic features (NIPS 2010). See also [ActionBank][]
 *  [Classemes, Picodes, and Meta-class features][Classemes_ Picodes_ and Meta-class features] – Software for extracting high-level image descriptors (ECCV 2010, NIPS 2011, CVPR 2012).

Large-Scale Learning

*  [Additive Kernels][] – Source code for fast additive kernel SVM classifiers (PAMI 2013).
 *  [LIBLINEAR][] – Library for large-scale linear SVM classification.
 *  [VLFeat][] – Implementation for Pegasos SVM and Homogeneous Kernel map.

Fast Indexing and Image Retrieval

*  [FLANN][] – Library for performing fast approximate nearest neighbor.
 *  [Kernelized LSH][] – Source code for Kernelized Locality-Sensitive Hashing (ICCV 2009).
 *  [ITQ Binary codes][] – Code for generation of small binary codes using Iterative Quantization and other baselines such as Locality-Sensitive-Hashing (CVPR 2011).
 *  [INRIA Image Retrieval][] – Efficient code for state-of-the-art large-scale image retrieval (CVPR 2011).

Object Detection

*  See [Part-based Models][] and [Convolutional Nets][] above.
 *  [Pedestrian Detection at 100fps][] – Very fast and accurate pedestrian detector (CVPR 2012).
 *  [Caltech Pedestrian Detection Benchmark][] – Excellent resource for pedestrian detection, with various links for state-of-the-art implementations.
 *  [OpenCV][OpenCV 3] – Enhanced implementation of Viola&Jones real-time object detector, with trained models for face detection.
 *  [Efficient Subwindow Search][] – Source code for branch-and-bound optimization for efficient object localization (CVPR 2008).

3D Recognition

*  [Point-Cloud Library][] – Library for 3D image and point cloud processing.

Action Recognition

*  [ActionBank][] – Source code for action recognition based on the ActionBank representation (CVPR 2012).
 *  [STIP Features][] – software for computing space-time interest point descriptors
 *  [Independent Subspace Analysis][] – Look for Stacked ISA for Videos (CVPR 2011)
 *  [Velocity Histories of Tracked Keypoints][] \- C++ code for activity recognition using the velocity histories of tracked keypoints (ICCV 2009)

Datasets

Attributes

*  [Animals with Attributes][] – 30,475 images of 50 animals classes with 6 pre-extracted feature representations for each image.
 *  [aYahoo and aPascal][] – Attribute annotations for images collected from Yahoo and Pascal VOC 2008.
 *  [FaceTracer][] – 15,000 faces annotated with 10 attributes and fiducial points.
 *  [PubFig][] – 58,797 face images of 200 people with 73 attribute classifier outputs.
 *  \[url=http://vis-[www.cs.umass.edu/lfw/][www.cs.umass.edu_lfw]\]LFW\[/url\] – 13,233 face images of 5,749 people with 73 attribute classifier outputs.
 *  [Human Attributes][Project 31] – 8,000 people with annotated attributes. Check also this [link][] for another dataset of human attributes.
 *  [SUN Attribute Database][] – Large-scale scene attribute database with a taxonomy of 102 attributes.
 *  [ImageNet Attributes][] – Variety of attribute labels for the ImageNet dataset.
 *  [Relative attributes][] – Data for OSR and a subset of PubFig datasets. Check also this [link][link 1] for the WhittleSearch data.
 *  [Attribute Discovery Dataset][] – Images of shopping categories associated with textual descriptions.

Fine-grained Visual Categorization

*  [Caltech-UCSD Birds Dataset][] – Hundreds of bird categories with annotated parts and attributes.
 *  [Stanford Dogs Dataset][] – 20,000 images of 120 breeds of dogs from around the world.
 *  [Oxford-IIIT Pet Dataset][] – 37 category pet dataset with roughly 200 images for each class. Pixel level trimap segmentation is included.
 *  [Leeds Butterfly Dataset][] – 832 images of 10 species of butterflies.
 *  [Oxford Flower Dataset][] – Hundreds of flower categories.

Face Detection

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

Face Recognition

*  [Face Recognition Homepage][] – Large collection of face recognition datasets.
 *  \[url=http://vis-[www.cs.umass.edu/lfw/][www.cs.umass.edu_lfw]\]LFW\[/url\] – UMass unconstrained face recognition dataset (13,000+ face images).
 *  [NIST Face Homepage][] – includes face recognition grand challenge (FRGC), vendor tests (FRVT) and others.
 *  [CMU Multi-PIE][] – contains more than 750,000 images of 337 people, with 15 different views and 19 lighting conditions.
 *  [FERET][] – Classical face recognition dataset.
 *  [Deng Cai’s face dataset in Matlab Format][Deng Cai_s face dataset in Matlab Format] – Easy to use if you want play with simple face datasets including Yale, ORL, PIE, and Extended Yale B.
 *  [SCFace][] – Low-resolution face dataset captured from surveillance cameras.

Handwritten Digits

*  [MNIST][Project 82] – large dataset containing a training set of 60,000 examples, and a test set of 10,000 examples.

Pedestrian Detection

*  [Caltech Pedestrian Detection Benchmark][] – 10 hours of video taken from a vehicle,350K bounding boxes for about 2.3K unique pedestrians.
 *  [INRIA Person Dataset][] – Currently one of the most popular pedestrian detection datasets.
 *  [ETH Pedestrian Dataset][] – Urban dataset captured from a stereo rig mounted on a stroller.
 *  [TUD-Brussels Pedestrian Dataset][] – Dataset with image pairs recorded in an crowded urban setting with an onboard camera.
 *  [PASCAL Human Detection][] – One of 20 categories in PASCAL VOC detection challenges.
 *  [USC Pedestrian Dataset][] – Small dataset captured from surveillance cameras.

Generic Object Recognition

*  [ImageNet][] – Currently the largest visual recognition dataset in terms of number of categories and images.
 *  [Tiny Images][] – 80 million 32x32 low resolution images.
 *  [Pascal VOC][PASCAL Human Detection] – One of the most influential visual recognition datasets.
 *  [Caltech 101][] / [Caltech 256][] – Popular image datasets containing 101 and 256 object categories, respectively.
 *  [MIT LabelMe][] – Online annotation tool for building computer vision databases.

Scene Recognition

*  [MIT SUN Dataset][] – MIT scene understanding dataset.
 *  [UIUC Fifteen Scene Categories][] – Dataset of 15 natural scene categories.

Feature Detection and Description

*  [VGG Affine Dataset][] – Widely used dataset for measuring performance of feature detection and description. Check[VLBenchmarks][]for an evaluation framework.

Action Recognition

*  [Benchmarking Activity Recognition][] – CVPR 2012 tutorial covering various datasets for action recognition.

RGBD Recognition

*  [RGB-D Object Dataset][] – Dataset containing 300 common household objects

Reference:

\[1\]: [http://rogerioferis.com/VisualRecognitionAndSearch/Resources.html][http_rogerioferis.com_VisualRecognitionAndSearch_Resources.html]

[Link 1]: http://lib.csdn.net/base/computervison
[Link 2]: http://lib.csdn.net/base/machinelearning
[Demo program]: http://www.cs.ubc.ca/~lowe/keypoints/siftDemoV4.zip
[SIFT Library]: http://blogs.oregonstate.edu/hess/code/sift/
[VLFeat]: http://www.vlfeat.org/
[Project]: http://www.cs.cmu.edu/~yke/pcasift/
[Project 1]: http://www.ipol.im/pub/algo/my_affine_sift/
[OpenSURF]: http://www.chrisevansdev.com/computer-vision-opensurf.html
[Matlab Wrapper]: http://www.maths.lth.se/matematiklth/personal/petter/surfmex.php
[Oxford project]: http://www.robots.ox.ac.uk/~vgg/research/affine/
[Code]: http://www.robots.ox.ac.uk/~vgg/software/MKL/
[Oxford implementation]: http://www.robots.ox.ac.uk/~vgg/software/SelfSimilarity/
[Code 1]: http://www.vision.ee.ethz.ch/~calvin/gss/selfsim_release1.0.tgz
[INRIA Object Localization Toolkit]: http://www.navneetdalal.com/software
[OLT toolkit for Windows]: http://www.computing.edu.au/~12482661/hog.html
[Project 2]: http://people.csail.mit.edu/torralba/code/spatialenvelope/
[Project 3]: http://www.eecs.berkeley.edu/Research/Projects/CS/vision/shape/sc_digits.html
[Project 4]: http://koen.me/research/colordescriptors/
[Code 2]: http://www.robots.ox.ac.uk/~vgg/research/caltech/phog/phog.zip
[Project 5]: http://www.nada.kth.se/cvap/abstracts/cvap284.html
[Code 3]: http://www.irisa.fr/vista/Equipe/People/Laptev/download/stip-1.1-winlinux.zip
[Project 6]: http://vision.cs.utexas.edu/projects/bplr/bplr.html
[Code 4]: http://www.wisdom.weizmann.ac.il/~bagon/matlab_code/whistc.tar.gz
[Paper]: http://www.cs.nthu.edu.tw/~htchen/hipd_cvpr09.pdf
[Code 5]: http://740-2.cs.nthu.edu.tw/~htchen/hipd/hist_corner.zip
[OpenCV]: http://lib.csdn.net/base/opencv
[Project 7]: http://intuitionlogic.com/post/2011/04/11/A-OpenCV-C++-implementation-of-Local-Self-Similarity-Descriptors.aspx
[Project 8]: http://faculty.ucmerced.edu/mhyang/cvpr10_fsr.html
[Project 9]: http://kiwi.cs.dal.ca/~dparks/CornerDetection/index.htm
[Project 10]: http://www6.in.tum.de/Main/ResearchAgast
[Project 11]: http://files.is.tue.mpg.de/jgall/projects/facialfeatures/facialfeatures.html
[code]: http://groups.inf.ed.ac.uk/calvin/gss/selfsim_release1.0.tgz
[Project 12]: http://image.ntua.gr/iva/research/wash/
[Project 13]: http://soc.fudan.edu.cn/vip/projects/gradproj/wiki/HOG%E4%BB%A3%E7%A0%81
[Project 14]: http://www.cs.ucla.edu/~roozbehm/cs7495/report.html
[Matlab code]: http://www.cis.upenn.edu/~jshi/software/
[Matlab code 1]: http://www.cs.sfu.ca/~mori/research/superpixels/
[C_ code]: http://people.cs.uchicago.edu/~pff/segment/
[Matlab wrapper]: http://www.mathworks.com/matlabcentral/fileexchange/25866-efficient-graph-based-image-segmentation
[EDISON C_ code]: http://coewww.rutgers.edu/riul/research/code/EDISON/index.html
[Matlab wrapper 1]: http://www.wisdom.weizmann.ac.il/~bagon/matlab_code/edison_matlab_interface.tar.gz
[Resources]: http://www.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/resources.html
[Matlab code 32bit]: http://www.cs.toronto.edu/~babalex/turbopixels_code.tar.gz
[Matlab code 64bit]: http://www.cs.toronto.edu/~babalex/TurboPixels64.rar
[Updated code]: http://www.cs.toronto.edu/~babalex/superpixels_update.tgz
[VLFeat 1]: http://www.vlfeat.org/overview/quickshift.html
[Project 15]: http://ivrgwww.epfl.ch/supplementary_material/RK_SLICSuperpixels/index.html
[Project 16]: http://perception.csl.uiuc.edu/coding/image_segmentation/
[Project 17]: http://www.cs.berkeley.edu/~smaji/projects/biasedNcuts/
[Project 18]: http://vision.ai.uiuc.edu/segmentation
[Code 6]: http://www.umiacs.umd.edu/~mingyliu/src/ers_matlab_wrapper_v0.1.zip
[Paper 1]: http://www.csd.uwo.ca/faculty/olga/Papers/pami01_final.pdf
[Code 7]: http://vision.csd.uwo.ca/code/gco-v3.0.zip
[Paper 2]: http://www.csd.uwo.ca/~schmidtf/pdf/schmidt_et_al_cvpr09.pdf
[Code 8]: http://vision.csd.uwo.ca/code/PlanarCut-v1.0.zip
[Paper 3]: http://www.cns.bu.edu/~lgrady/grady2006isoperimetric.pdf
[Code 9]: http://www.cns.bu.edu/~lgrady/grady2006isoperimetric_code.zip
[Paper 4]: http://www.cns.bu.edu/~lgrady/grady2006random.pdf
[Code 10]: http://www.cns.bu.edu/~lgrady/random_walker_matlab_code.zip
[Code 11]: http://pub.ist.ac.at/~vnk/software/blossom5-v2.03.src.tar.gz%20%20http:/pub.ist.ac.at/~vnk/software/blossom5-v2.03.src.tar.gz
[Paper 5]: http://www.csd.uwo.ca/~yuri/Papers/pami04.pdf
[Code 12]: http://pub.ist.ac.at/~vnk/software/maxflow-v3.01.src.tar.gz
[Project 19]: http://www.robots.ox.ac.uk/~vgg/software/iseg/
[Code 13]: http://www.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/BSR/BSR_source.tgz
[Project 20]: http://www.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/biasedNcuts/
[Project 21]: http://vision.csd.uwo.ca/code/
[Project 22]: http://www.ipol.im/pub/art/2012/g-cv/
[Project 23]: http://www.cs.ubc.ca/~mitchell/ToolboxLS/index.html
[Project 24]: http://www4.comp.polyu.edu.hk/~cslzhang/RD/RD.htm
[Paper 6]: http://www4.comp.polyu.edu.hk/~cskhzhang/J_papers/ICV.pdf
[Code 14]: http://www4.comp.polyu.edu.hk/~cskhzhang/J_papers/ICV.rar
[Paper 7]: http://www4.comp.polyu.edu.hk/~cskhzhang/J_papers/ICIP10_SVMLS.pdf
[Code 15]: http://www4.comp.polyu.edu.hk/~cskhzhang/J_papers/SVMLS_v0.rar
[Project 25]: http://www.engr.uconn.edu/~cmli/
[cod]: http://groups.inf.ed.ac.uk/calvin/classcut/ClassCut-release_v1.0.zip
[Project 26]: http://www.vision.ee.ethz.ch/~vamichae/seeds/
[other]: http://www.mvdblive.org/seeds/
[Project 27]: http://people.csail.mit.edu/torralba/shortCourseRLOC/boosting/boosting.html
[Project 28]: http://pascal.inrialpes.fr/soft/olt/
[Project 29]: http://people.cs.uchicago.edu/~pff/latent/
[Project 30]: http://people.cs.uchicago.edu/~rbg/star-cascade/
[Project 31]: http://www.eecs.berkeley.edu/~lbourdev/poselets/
[Project 32]: http://www.vision.ee.ethz.ch/~bleibe/code/ism.html
[Project 33]: http://pr.willowgarage.com/wiki/Face_detection
[Paper 8]: http://vision.eecs.ucf.edu/papers/01512057.pdf
[Code 16]: http://vision.eecs.ucf.edu/Code/Background.zip
[Project 34]: http://www.robots.ox.ac.uk/~vgg/software/hands/
[Paper 9]: http://www.eecs.berkeley.edu/Research/Projects/CS/vision/reconstruction/BarronMalikECCV2012.pdf
[Code 17]: http://www.cs.berkeley.edu/~barron/BarronMalikECCV2012_code.zip
[Project 35]: http://people.cs.uchicago.edu/~rbg/latent/
[Project 36]: http://campar.cs.tum.edu/Main/StefanHinterstoisser
[Project 37]: http://www.ipol.im/
[Project 38]: http://www.ipol.im/pub/pre/21/
[Project 39]: http://homes.cs.washington.edu/~rahul/data/WheresWaldo.html
[Project 40]: http://files.is.tue.mpg.de/jgall/projects/houghMC/houghMC.html
[Project 41]: http://files.is.tue.mpg.de/jgall/projects/houghforest/houghforest.html
[Project 42]: http://vision.cse.psu.edu/data/data.shtml
[Matlab code 2]: http://www.saliencytoolbox.net/
[Project 43]: http://ivrgwww.epfl.ch/supplementary_material/RK_CVPR09/index.html
[Project 44]: http://ivrg.epfl.ch/supplementary_material/RK_ICIP2010/index.html
[Matlab code 3]: http://www.cse.yorku.ca/~neil/AIM.zip
[Matlab code 4]: http://webee.technion.ac.il/labs/cgm/Computer-Graphics-Multimedia/Software/Saliency/Saliency.html
[Matlab code 5]: http://www.klab.caltech.edu/~harel/share/gbvs.php
[Matlab code 6]: http://www.klab.caltech.edu/~xhou/projects/spectralResidual/spectralresidual.html
[Matlab code 7]: http://www.cse.oulu.fi/MVG/Downloads/saliency
[Matlab code 8]: http://cseweb.ucsd.edu/~l6zhang/
[Code 18]: http://www.svcl.ucsd.edu/projects/saliency/
[Project 45]: http://people.csail.mit.edu/tjudd/WherePeopleLook/index.html
[Project 46]: http://cg.cs.tsinghua.edu.cn/people/~cmm/saliency/
[Project 47]: http://ice.dlut.edu.cn/lu/Project/TIP_scm/TIP_scm.htm
[Paper 10]: http://faculty.ucmerced.edu/mhyang/papers/cvpr12a.pdf
[Code 19]: http://faculty.ucmerced.edu/mhyang/code/top-down-saliency.zip
[Code 20]: http://www.klab.caltech.edu/~xhou/projects/dva/dva.html
[Project 48]: http://people.csail.mit.edu/jjl/libpmk/
[Code 21]: http://www.cs.unc.edu/~lazebnik/research/SpatialPyramid.zip
[Project 49]: http://www.ifp.illinois.edu/~jyang29/LLC.htm
[Matlab code 9]: http://www.ifp.illinois.edu/~jyang29/codes/CVPR10-LLC.rar
[Project 50]: http://www.ifp.illinois.edu/~jyang29/ScSPM.htm
[Matlab code 10]: http://www.ifp.illinois.edu/~jyang29/codes/CVPR09-ScSPM.rar
[Project 51]: http://www.robots.ox.ac.uk/~vgg/research/texclass/index.html
[Project 52]: http://www.vision.ee.ethz.ch/~pgehler/projects/iccv09/index.html
[Code 22]: http://www.cs.unc.edu/~jtighe/Papers/ECCV10/eccv10-jtighe-code.zip
[Matlab code 11]: http://www.wisdom.weizmann.ac.il/~bagon/matlab_code/LargeScaleCC1.0.tar.gz
[Project 53]: http://www.wisdom.weizmann.ac.il/~vision/SketchTheCommon
[Project 54]: http://www.vision.caltech.edu/lihi/Demos/SelfTuningClustering.html
[Code 23]: http://www.vision.caltech.edu/lihi/Demos/SelfTuning/ZPclustering.zip
[Paper 11]: http://www.wisdom.weizmann.ac.il/~levina/papers/assisted-eccv04.pdf
[Code 24]: http://www.wisdom.weizmann.ac.il/~levina/papers/reflections.zip
[Project 55]: http://www.robots.ox.ac.uk/~vgg/research/texclass/filters.html#download
[Project 56]: http://ivrg.epfl.ch/supplementary_material/RK_SLICSuperpixels/
[Code 25]: http://people.csail.mit.edu/alevin/matting.tar.gz
[Project 57]: http://www.vision.huji.ac.il/SpectralMatting/
[Code 26]: http://www.mathworks.com/matlabcentral/fileexchange/31412
[Project 58]: http://www.ai.mit.edu/projects/vsam/Tracking/index.html
[Paper 12]: http://faculty.ucmerced.edu/mhyang/papers/tip12_pls_tracking.pdf
[Code 27]: http://faculty.ucmerced.edu/mhyang/code/PLS_tracker_tip.zip
[Paper 13]: http://faculty.ucmerced.edu/mhyang/papers/pami11b.pdf
[Code 28]: http://vision.ucsd.edu/~bbabenko/project_miltrack.shtml
[Project 59]: http://www.cise.ufl.edu/~smshahed/tracking.htm
[Project 60]: http://www.cs.toronto.edu/~dross/ivt/
[Project 61]: http://www4.comp.polyu.edu.hk/~cslzhang/CT/CT.htm
[Project 62]: http://faculty.ucmerced.edu/mhyang/project/cvpr12_scm.htm
[Project 63]: http://faculty.ucmerced.edu/mhyang/project/cvpr12_jia_project.htm
[Paper 14]: http://faculty.ucmerced.edu/mhyang/papers/wacv12a.pdf
[Code 29]: http://faculty.ucmerced.edu/mhyang/code/wacv12a_code.zip
[Project 64]: http://faculty.ucmerced.edu/mhyang/papers/iccv11a.html
[Paper 15]: http://faculty.ucmerced.edu/mhyang/papers/bmvc11a.pdf
[Code 30]: http://faculty.ucmerced.edu/mhyang/code/BMVC11-HSSL-package.zip
[Paper 16]: http://faculty.ucmerced.edu/mhyang/papers/fg11a.pdf
[Code 31]: http://faculty.ucmerced.edu/mhyang/code/fg11_omsit.zip
[Project 65]: http://c2inet.sce.ntu.edu.sg/Jianxin/
[Project 66]: http://dsp.rice.edu/cs
[Project 67]: http://www.robots.ox.ac.uk/~cbibby/index.shtml
[Project 68]: http://info.ee.surrey.ac.uk/Personal/Z.Kalal/
[OpenTLD_C_ Code]: https://github.com/arthurv/OpenTLD
[Project 69]: http://ilab.cs.ucsb.edu/index.php/component/content/article/12/29
[Project 70]: http://files.is.tue.mpg.de/jgall/projects/stochGPLVM/stochGPLVM.html
[Project 71]: http://kinecttoolbox.codeplex.com/
[Project 72]: http://www.openni.org/
[Resource]: http://blog.csdn.net/zouxy09/article/details/8145688
[code 1]: http://makematics.com/code/FingerTracker/
[Paper 17]: http://www.wisdom.weizmann.ac.il/~ronen/papers/Simakov%20Frolova%20Basri%20-%20Dense%20Shape%20Reconstruction%20Under%20Arbitrary%20Unknown%20Lighting.pdf
[Code 32]: http://www.wisdom.weizmann.ac.il/~bagon/matlab_code/SFB_matlab1.0.tar.gz
[Code 33]: http://vision.eecs.ucf.edu/shadsrc.html
[Project 73]: http://vision.eecs.ucf.edu/combsrc.html
[Code 34]: http://vision.eecs.ucf.edu/projects/ShapeFromShading/combine.tar.Z
[Paper 18]: http://vision.eecs.ucf.edu/papers/shah/99/ZTCS99.pdf
[Code 35]: http://vision.eecs.ucf.edu/projects/ShapeFromShading/SFS_Survey_1_00.tar.gz
[Project 74]: http://lear.inrialpes.fr/people/klaeser/research_hog3d
[Code 36]: http://lear.inrialpes.fr/people/klaeser/software_3d_video_descriptor
[Paper 19]: http://www.cs.cornell.edu/~rdz/papers/kz-eccv02-recon.pdf
[Code 37]: http://pub.ist.ac.at/~vnk/software/match-v3.4.src.tar.gz
[Paper 20]: http://www.cs.ucf.edu/~vision
[Code 38]: http://www.ee.cityu.edu.hk/~syyuen/Public/SfS/PRL_Perspective_FMM.zip
[Project 75]: http://www.eecs.berkeley.edu/Research/Projects/CS/vision/reconstruction/
[Code 39]: http://faculty.ucmerced.edu/mhyang/code/PackagedTrackingCode.tar.gz
[Project 76]: http://ai.stanford.edu/~asaxena/reconstruction3d/
[Link 3]: http://lib.csdn.net/base/datastructure
[Matlab class]: http://www.wisdom.weizmann.ac.il/~bagon/matlab_code/ann_wrapper_Mar2012.tar.gz
[ANN library]: http://www.cs.umd.edu/~mount/ANN/
[code 2]: http://www.wisdom.weizmann.ac.il/~bagon/matlab_code/weight_sample.tar.gz
[Code 40]: http://www.robots.ox.ac.uk/~vgg/software/pLSA/pLSA_demo.tgz
[Project 77]: http://www.robots.ox.ac.uk/~vgg/software/fastann/
[Project 78]: http://www.cs.berkeley.edu/~smaji/projects/fiksvm/
[Code 41]: http://osmot.cs.cornell.edu/svm_light/
[Net]: http://deeplearning.net/
[Project 79]: http://cs.nyu.edu/~fergus/tutorials/deep_learning_cvpr12/
[Project 80]: http://www.codeproject.com/KB/library/NeuralNetRecognition.aspx
[Project 81]: http://www.cs.toronto.edu/~hinton/MatlabForSciencePaper.html
[Project 82]: http://yann.lecun.com/exdb/mnist/
[Project 83]: http://www.ersatz1.com/
[Project 84]: http://www.cs.nyu.edu/~yann/research/deep/
[Project 85]: http://www.ics.forth.gr/~lourakis/sparseLM/
[Java]: http://lib.csdn.net/base/javase
[Project 86]: http://www.cs.waikato.ac.nz/ml/weka/
[Video]: http://vipl.ict.ac.cn/News/academic-report-tutorial-deep-learning-dr-kai-yu
[Matlab Tool]: http://www.mathworks.cn/matlabcentral/fileexchange/24291
[Wedsite]: http://yann.lecun.com/exdb/publis/index.html#lecun-98
[Project 87]: http://yann.lecun.com/exdb/lenet/index.html
[Website]: http://www.cs.toronto.edu/~hinton/
[Code 42]: http://lear.inrialpes.fr/people/guillaumin/code.php#mildml
[Project 88]: http://redwood.berkeley.edu/bruno/sparsenet/
[Software]: http://lear.inrialpes.fr/software
[Project 89]: http://lear.inrialpes.fr/people/wang/dense_trajectories
[Code 43]: http://lear.inrialpes.fr/people/wang/download/dense_trajectory_release.tar.gz
[Project 90]: http://www.eecs.berkeley.edu/Research/Projects/CS/vision/shape/action/
[Paper 21]: http://www.eecs.berkeley.edu/Research/Projects/CS/vision/shape/glam-cvpr09.pdf
[Code 44]: http://www.eecs.berkeley.edu/Research/Projects/CS/vision/shape/glam_cvpr09_v2.zip
[Project 91]: http://www.vision.ee.ethz.ch/~calvin/articulated_human_pose_estimation_code/
[Paper 22]: http://faculty.ucmerced.edu/mhyang/papers/cvpr07a.pdf
[Code 45]: http://www.cise.ufl.edu/~smshahed/cvpr07_fast_human_pose.zip
[Paper 23]: http://faculty.ucmerced.edu/mhyang/papers/accv09a.pdf
[Code 46]: http://faculty.ucmerced.edu/mhyang/code/accv09_pose.zip
[Project 92]: http://www.ee.oulu.fi/~jkannala/quasidense/quasidense.html
[Project 93]: http://gesture.chalearn.org/data/sample-code
[Project 94]: http://files.is.tue.mpg.de/jgall/projects/RFhead/RFhead.html
[Project 95]: http://files.is.tue.mpg.de/jgall/projects/ARforPose/ARforPose.html
[Project 96]: http://files.is.tue.mpg.de/jgall/projects/houghAR/houghAR.html
[Project 97]: http://www.openu.ac.il/home/hassner/projects/MIP/
[Project 98]: http://groups.inf.ed.ac.uk/calvin/articulated_human_pose_estimation_code/
[code 3]: http://groups.inf.ed.ac.uk/calvin/release-learn-shapes-v1.3.tgz
[Project 99]: http://www.robots.ox.ac.uk/~vgg/software/UpperBody/index.html
[Project 100]: http://movement.stanford.edu/learning-nr-shape/
[Project 101]: http://cs.brown.edu/~pff/dt/
[Project 102]: http://www.cs.cmu.edu/~cil/vision.html
[code 4]: http://groups.inf.ed.ac.uk/calvin/efficientAppDistances/releaseEfficientAppDistances.zip
[code 5]: http://groups.inf.ed.ac.uk/calvin/ReleasedCode/image_exploration_v1.1.tgz
[Project 103]: http://people.csail.mit.edu/celiu/motionmag/motionmag.html
[Project 104]: http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/MANDUCHI1/Bilateral_Filtering.html
[Project 105]: http://people.csail.mit.edu/sparis/bf/
[Project 106]: http://egt.dii.unisi.it/
[Code 47]: http://egt.dii.unisi.it/download/EGT_v1p3.zip
[Project 107]: http://www.cs.stonybrook.edu/~kyamagu/mexopencv/
[Project 108]: http://leenissen.dk/fann/wp/
[Code 48]: http://code.google.com/p/finger-detection-and-gesture-recognition/downloads/list
[Project 109]: http://www.javacodegeeks.com/2012/12/hand-and-finger-detection-using-javacv.html?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+JavaCodeGeeks+%28Java+Code+Geeks%29
[Code 49]: http://forum.openframeworks.cc/index.php?topic=1916.0
[Project 110]: http://people.csail.mit.edu/celiu/LabelTransfer/code.html
[Project 111]: http://perception.inrialpes.fr/~chari/myweb/Software/
[Project 112]: http://people.csail.mit.edu/celiu/SIFTflow/
[Project 113]: http://www.ces.clemson.edu/~stb/klt/
[Project 114]: http://www.mathworks.cn/cn/help/vision/examples/tracking-cars-using-optical-flow.html
[Project 115]: http://ps.is.tue.mpg.de/person/black#tabs-code
[Project 116]: https://www.ceremade.dauphine.fr/~peyre/numerical-tour/tours/multidim_5_opticalflow/#37
[Project 117]: http://people.csail.mit.edu/celiu/OpticalFlow/
[Project 118]: http://vision.middlebury.edu/flow/
[Project 119]: http://lmb.informatik.uni-freiburg.de/resources/software.php
[Project 120]: http://www.jonathanmugan.com/GraphicsProject/OpticalFlow/
[Paper 24]: http://www.ee.columbia.edu/~wliu/CVPR08_ssml.pdf
[code 6]: http://www.ee.columbia.edu/~wliu/SSMetric.zip
[Project 121]: http://people.csail.mit.edu/billf/project%20pages/sresCode/Markov%20Random%20Fields%20for%20Super-Resolution.html
[Project 122]: http://vision.middlebury.edu/MRF/
[Project 123]: http://www.visionbib.com/bibliography/motion-i763.html
[Project 124]: http://www2.ulg.ac.be/telecom/publi/publications/mvd/VanDroogenbroeck2012Background/index.html
[Project 125]: http://www.na.icar.cnr.it/~maddalena.l/MODLab/SoftwareSOBS.html
[.NET]: http://lib.csdn.net/base/dotnet
[Project 126]: http://www.changedetection.net/
[Project 127]: http://www2.ulg.ac.be/telecom/research/vibe/
[Project 128]: http://www.umiacs.umd.edu/~knkim/UMD-BGS/index.html
[Project 129]: http://www.codeproject.com/Articles/10248/Motion-Detection-Algorithms
[Project 130]: http://www.vis.uni-stuttgart.de/index.php?id=sabs
[Project 131]: http://www.mathworks.cn/cn/help/vision/motion-analysis-and-tracking.html
[Modern features_ Software]: https://docs.google.com/viewer?a=v&pid=sites&srcid=ZGVmYXVsdGRvbWFpbnxlY2N2MTJmZWF0dXJlc3xneDo3ZDllMzVhMDA4YzEzNmU2
[VLFeat hands-on session training]: https://sites.google.com/site/eccv12features/
[OpenCV 1]: http://opencv.org/
[FAST]: http://www.edwardrosten.com/work/fast.html
[BRIEF]: http://cvlab.epfl.ch/software/brief/
[ORB]: http://docs.opencv.org/modules/features2d/doc/feature_detection_and_description.html
[BRISK]: http://www.asl.ethz.ch/people/lestefan/personal/BRISK
[FREAK]: http://www.ivpe.com/freak.htm
[OpenCV 2]: http://docs.opencv.org/modules/nonfree/doc/feature_detection.html
[Original code]: http://www.cs.ubc.ca/~lowe/keypoints/
[GPU implementation]: http://cs.unc.edu/~ccwu/siftgpu/
[OpenSIFT]: http://robwhess.github.com/opensift/
[Herbert Bay_s code]: http://www.vision.ee.ethz.ch/~surf/
[GPU-SURF]: http://www.visual-experiments.com/demos/gpusurf/
[LIOP descriptor]: http://vision.ia.ac.cn/Students/wzh/publication/liop/index.html
[Local Symmetry Features]: http://www.cs.cornell.edu/projects/symfeat/
[CENTRIST]: https://sites.google.com/site/wujx2001/home
[VGG Feature Encoding Toolkit]: http://www.robots.ox.ac.uk/~vgg/software/enceval_toolkit/
[Spatial Pyramid Matching]: http://www.cs.illinois.edu/homes/slazebni/
[EBLearn]: http://eblearn.sourceforge.net/
[Torch7]: http://www.torch.ch/
[Deep Learning]: http://deeplearning.net/software_links/
[Efficient Deformable Part-Based Detector]: http://vision.mas.ecp.fr/Personnel/iasonas/dpms.html
[Accelerated Deformable Part Model]: http://www.idiap.ch/~cdubout/coding.html
[Coarse-to-Fine Deformable Part Model]: http://iselab.cvc.uab.es/CoarseToFine
[Part-based Face Detector and Pose Estimation]: http://www.ics.uci.edu/~xzhu/face/
[Relative Attributes]: http://ttic.uchicago.edu/~dparikh/relative.html#code
[Object Bank]: http://vision.stanford.edu/projects/objectbank/
[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
[Additive Kernels]: http://ttic.uchicago.edu/~smaji/projects/fiksvm/
[LIBLINEAR]: http://www.csie.ntu.edu.tw/~cjlin/liblinear/
[FLANN]: http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN
[Kernelized LSH]: http://www.cse.ohio-state.edu/~kulis/klsh/klsh.htm
[ITQ Binary codes]: http://www.unc.edu/~yunchao/itq.htm
[INRIA Image Retrieval]: http://lear.inrialpes.fr/src/inria_fisher/
[Part-based Models]: http://rogerioferis.com/VisualRecognitionAndSearch/Resources.html#parts
[Convolutional Nets]: http://rogerioferis.com/VisualRecognitionAndSearch/Resources.html#convnets
[Pedestrian Detection at 100fps]: https://bitbucket.org/rodrigob/doppia
[Caltech Pedestrian Detection Benchmark]: http://www.vision.caltech.edu/Image_Datasets/CaltechPedestrians/
[OpenCV 3]: http://docs.opencv.org/trunk/modules/objdetect/doc/cascade_classification.html?highlight=face%20detection
[Efficient Subwindow Search]: https://sites.google.com/site/christophlampert/software
[Point-Cloud Library]: http://www.pointclouds.org/
[STIP Features]: http://www.di.ens.fr/~laptev/download.html
[Independent Subspace Analysis]: http://ai.stanford.edu/~quocle/
[Velocity Histories of Tracked Keypoints]: http://www.cs.rochester.edu/~rmessing/uradl/
[Animals with Attributes]: http://attributes.kyb.tuebingen.mpg.de/
[aYahoo and aPascal]: http://vision.cs.uiuc.edu/attributes/
[FaceTracer]: http://www.cs.columbia.edu/CAVE/databases/facetracer/
[PubFig]: http://www.cs.columbia.edu/CAVE/databases/pubfig/
[www.cs.umass.edu_lfw]: http://www.cs.umass.edu/lfw/
[link]: https://sharma.users.greyc.fr/hatdb/
[SUN Attribute Database]: http://cs.brown.edu/~gen/sunattributes.html
[ImageNet Attributes]: http://www.image-net.org/download-attributes
[Relative attributes]: http://ttic.uchicago.edu/~dparikh/relative.html#data
[link 1]: http://vision.cs.utexas.edu/whittlesearch/
[Attribute Discovery Dataset]: http://tamaraberg.com/attributesDataset/index.html
[Caltech-UCSD Birds Dataset]: http://www.vision.caltech.edu/visipedia/CUB-200-2011.html
[Stanford Dogs Dataset]: http://vision.stanford.edu/aditya86/ImageNetDogs/
[Oxford-IIIT Pet Dataset]: http://www.robots.ox.ac.uk/~vgg/data/pets/
[Leeds Butterfly Dataset]: http://www.comp.leeds.ac.uk/scs6jwks/dataset/leedsbutterfly/
[Oxford Flower Dataset]: http://www.robots.ox.ac.uk/~vgg/data/flowers/
[www.cs.umass.edu_fddb]: http://www.cs.umass.edu/fddb/
[CMU_MIT]: http://vasc.ri.cmu.edu/idb/html/face/frontal_images/index.html
[Face Recognition Homepage]: http://www.face-rec.org/databases/
[NIST Face Homepage]: http://www.nist.gov/itl/iad/ig/face.cfm
[CMU Multi-PIE]: http://www.multipie.org/
[FERET]: http://www.nist.gov/itl/iad/ig/colorferet.cfm
[Deng Cai_s face dataset in Matlab Format]: http://www.cad.zju.edu.cn/home/dengcai/Data/FaceData.html
[SCFace]: http://www.scface.org/
[INRIA Person Dataset]: http://pascal.inrialpes.fr/data/human/
[ETH Pedestrian Dataset]: http://www.vision.ee.ethz.ch/~aess/dataset/
[TUD-Brussels Pedestrian Dataset]: http://www.d2.mpi-inf.mpg.de/tud-brussels
[PASCAL Human Detection]: http://pascallin.ecs.soton.ac.uk/challenges/VOC/
[USC Pedestrian Dataset]: http://iris.usc.edu/Vision-Users/OldUsers/bowu/DatasetWebpage/dataset.html
[ImageNet]: http://www.image-net.org/
[Tiny Images]: http://groups.csail.mit.edu/vision/TinyImages/
[Caltech 101]: http://www.vision.caltech.edu/Image_Datasets/Caltech101/
[Caltech 256]: http://www.vision.caltech.edu/Image_Datasets/Caltech256/
[MIT LabelMe]: http://new-labelme.csail.mit.edu/Release3.0/index.php
[MIT SUN Dataset]: http://groups.csail.mit.edu/vision/SUN/
[UIUC Fifteen Scene Categories]: http://www-cvr.ai.uiuc.edu/ponce_grp/data/
[VGG Affine Dataset]: http://www.robots.ox.ac.uk/~vgg/data/data-aff.html
[VLBenchmarks]: http://www.vlfeat.org/benchmarks/index.html
[Benchmarking Activity Recognition]: http://rogerioferis.com/VisualRecognitionAndSearch/material/LiuFerisSunTutorial.pdf
[RGB-D Object Dataset]: http://www.cs.washington.edu/rgbd-dataset/index.html
[http_rogerioferis.com_VisualRecognitionAndSearch_Resources.html]: http://rogerioferis.com/VisualRecognitionAndSearch/Resources.html