一、特征提取Feature Extraction：
· SIFT [1] [][] []
· PCA-SIFT [2] []
· Affine-SIFT [3] []
· SURF [4] [] []
· Affine Covariant Features [5] []
· MSER [6] [] []
· Geometric Blur [7] []
· Local Self-Similarity Descriptor [8] []
· Global and Efficient Self-Similarity [9] []
· Histogram of Oriented Graidents [10] [] []
· GIST [11] []
· Shape Context [12] []
· Color Descriptor [13] []
· Pyramids of Histograms of Oriented Gradients []
· Space-Time Interest Points (STIP) [14][] []
· Boundary Preserving Dense Local Regions [15][]
· Weighted Histogram[]
· Histogram-based Interest Points Detectors[][]
· An OpenCV - C++ implementation of Local Self Similarity Descriptors []
· Fast Sparse Representation with Prototypes[]
· Corner Detection []
· AGAST Corner Detector: faster than FAST and even FAST-ER[]
· Real-time Facial Feature Detection using Conditional Regression Forests[]
· Global and Efficient Self-Similarity for Object Classification and Detection[]
· WαSH: Weighted α-Shapes for Local Feature Detection[]
· HOG[]
· Online Selection of Discriminative Tracking Features[]
二、图像分割Image Segmentation：
· Normalized Cut [1] []
· Gerg Mori’ Superpixel code [2] []
· Efficient Graph-based Image Segmentation [3] [] []
· Mean-Shift Image Segmentation [4] [] []
· OWT-UCM Hierarchical Segmentation [5] []
· Turbepixels [6] [] [] []
· Quick-Shift [7] []
· SLIC Superpixels [8] []
· Segmentation by Minimum Code Length [9] []
· Biased Normalized Cut [10] []
· Segmentation Tree [11-12] []
· Entropy Rate Superpixel Segmentation [13] []
· Fast Approximate Energy Minimization via Graph Cuts[][]
· Efficient Planar Graph Cuts with Applications in Computer Vision[][]
· Isoperimetric Graph Partitioning for Image Segmentation[][]
· Random Walks for Image Segmentation[][]
· Blossom V: A new implementation of a minimum cost perfect matching algorithm[]
· An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Computer Vision[][]
· Geodesic Star Convexity for Interactive Image Segmentation[]
· Contour Detection and Image Segmentation Resources[][]
· Biased Normalized Cuts[]
· Max-flow/min-cut[]
· Chan-Vese Segmentation using Level Set[]
· A Toolbox of Level Set Methods[]
· Re-initialization Free Level Set Evolution via Reaction Diffusion[]
· Improved C-V active contour model[][]
· A Variational Multiphase Level Set Approach to Simultaneous Segmentation and Bias Correction[][]
· Level Set Method Research by Chunming Li[]
· ClassCut for Unsupervised Class Segmentation[e]
· SEEDS: Superpixels Extracted via Energy-Driven Sampling ][]
三、目标检测Object Detection：
· A simple object detector with boosting []
· INRIA Object Detection and Localization Toolkit [1] []
· Discriminatively Trained Deformable Part Models [2] []
· Cascade Object Detection with Deformable Part Models [3] []
· Poselet [4] []
· Implicit Shape Model [5] []
· Viola and Jones’s Face Detection [6] []
· Bayesian Modelling of Dyanmic Scenes for Object Detection[][]
· Hand detection using multiple proposals[]
· Color Constancy, Intrinsic Images, and Shape Estimation[][]
· Discriminatively trained deformable part models[]
· Gradient Response Maps for Real-Time Detection of Texture-Less Objects: LineMOD []
· Image Processing On Line[]
· Robust Optical Flow Estimation[]
· Where's Waldo: Matching People in Images of Crowds[]
· Scalable Multi-class Object Detection[]
· Class-Specific Hough Forests for Object Detection[]
· Deformed Lattice Detection In Real-World Images[]
· Discriminatively trained deformable part models[]
四、显著性检测Saliency Detection：
· Itti, Koch, and Niebur’ saliency detection [1] []
· Frequency-tuned salient region detection [2] []
· Saliency detection using maximum symmetric surround [3] []
· Attention via Information Maximization [4] []
· Context-aware saliency detection [5] []
· Graph-based visual saliency [6] []
· Saliency detection: A spectral residual approach. [7] []
· Segmenting salient objects from images and videos. [8] []
· Saliency Using Natural statistics. [9] []
· Discriminant Saliency for Visual Recognition from Cluttered Scenes. [10] []
· Learning to Predict Where Humans Look [11] []
· Global Contrast based Salient Region Detection [12] []
· Bayesian Saliency via Low and Mid Level Cues[]
· Top-Down Visual Saliency via Joint CRF and Dictionary Learning[][]
· Saliency Detection: A Spectral Residual Approach[]
五、图像分类、聚类Image Classification, Clustering
· Pyramid Match [1] []
· Spatial Pyramid Matching [2] []
· Locality-constrained Linear Coding [3] [] []
· Sparse Coding [4] [] []
· Texture Classification [5] []
· Multiple Kernels for Image Classification [6] []
· Feature Combination [7] []
· SuperParsing []
· Large Scale Correlation Clustering Optimization[]
· Detecting and Sketching the Common[]
· Self-Tuning Spectral Clustering[][]
· User Assisted Separation of Reflections from a Single Image Using a Sparsity Prior[][]
· Filters for Texture Classification[]
· Multiple Kernel Learning for Image Classification[]
· SLIC Superpixels[]
六、抠图Image Matting
· A Closed Form Solution to Natural Image Matting []
· Spectral Matting []
· Learning-based Matting []
七、目标跟踪Object Tracking：
· A Forest of Sensors - Tracking Adaptive Background Mixture Models []
· Object Tracking via Partial Least Squares Analysis[][]
· Robust Object Tracking with Online Multiple Instance Learning[][]
· Online Visual Tracking with Histograms and Articulating Blocks[]
· Incremental Learning for Robust Visual Tracking[]
· Real-time Compressive Tracking[]
· Robust Object Tracking via Sparsity-based Collaborative Model[]
· Visual Tracking via Adaptive Structural Local Sparse Appearance Model[]
· Online Discriminative Object Tracking with Local Sparse Representation[][]
· Superpixel Tracking[]
· Learning Hierarchical Image Representation with Sparsity, Saliency and Locality[][]
· Online Multiple Support Instance Tracking [][]
· Visual Tracking with Online Multiple Instance Learning[]
· Object detection and recognition[]
· Compressive Sensing Resources[]
· Robust Real-Time Visual Tracking using Pixel-Wise Posteriors[]
· Tracking-Learning-Detection[][]
· the HandVu：vision-based hand gesture interface[]
· Learning Probabilistic Non-Linear Latent Variable Models for Tracking Complex Activities[]
八、Kinect：
· Kinect toolbox[]
· OpenNI[]
· zouxy09 CSDN Blog[]
· FingerTracker 手指跟踪[]
九、3D相关：
· 3D Reconstruction of a Moving Object[] []
· Shape From Shading Using Linear Approximation[]
· Combining Shape from Shading and Stereo Depth Maps[][]
· Shape from Shading: A Survey[][]
· A Spatio-Temporal Descriptor based on 3D Gradients (HOG3D)[][]
· Multi-camera Scene Reconstruction via Graph Cuts[][]
· A Fast Marching Formulation of Perspective Shape from Shading under Frontal Illumination[][]
· Reconstruction:3D Shape, Illumination, Shading, Reflectance, Texture[]
· Monocular Tracking of 3D Human Motion with a Coordinated Mixture of Factor Analyzers[]
· Learning 3-D Scene Structure from a Single Still Image[]
十、机器学习算法：
· Matlab class for computing Approximate Nearest Nieghbor (ANN) [ providing interface to]
· Random Sampling[]
· Probabilistic Latent Semantic Analysis (pLSA)[]
· FASTANN and FASTCLUSTER for approximate k-means (AKM)[]
· Fast Intersection / Additive Kernel SVMs[]
· SVM[]
· Ensemble learning[]
· Deep Learning[]
· Deep Learning Methods for Vision[]
· Neural Network for Recognition of Handwritten Digits[]
· Training a deep autoencoder or a classifier on MNIST digits[]
· THE MNIST DATABASE of handwritten digits[]
· Ersatz：deep neural networks in the cloud[]
· Deep Learning []
· sparseLM : Sparse Levenberg-Marquardt nonlinear least squares in C/C++[]
· Weka 3: Data Mining Software in Java[]
· Invited talk "A Tutorial on Deep Learning" by Dr. Kai Yu (余凯)[]
· CNN - Convolutional neural network class[]
· Yann LeCun's Publications[]
· LeNet-5, convolutional neural networks[]
· Training a deep autoencoder or a classifier on MNIST digits[]
· Deep Learning 大牛Geoffrey E. Hinton's HomePage[]
· Multiple Instance Logistic Discriminant-based Metric Learning (MildML) and Logistic Discriminant-based Metric Learning (LDML)[]
· Sparse coding simulation software[]
· Visual Recognition and Machine Learning Summer School[]
十一、目标、行为识别Object, Action Recognition：
· Action Recognition by Dense Trajectories[][]
· Action Recognition Using a Distributed Representation of Pose and Appearance[]
· Recognition Using Regions[][]
· 2D Articulated Human Pose Estimation[]
· Fast Human Pose Estimation Using Appearance and Motion via Multi-Dimensional Boosting Regression[][]
· Estimating Human Pose from Occluded Images[][]
· Quasi-dense wide baseline matching[]
· ChaLearn Gesture Challenge: Principal motion: PCA-based reconstruction of motion histograms[]
· Real Time Head Pose Estimation with Random Regression Forests[]
· 2D Action Recognition Serves 3D Human Pose Estimation[
· A Hough Transform-Based Voting Framework for Action Recognition[
· Motion Interchange Patterns for Action Recognition in Unconstrained Videos[
· 2D articulated human pose estimation software[]
· Learning and detecting shape models []
· Progressive Search Space Reduction for Human Pose Estimation[]
· Learning Non-Rigid 3D Shape from 2D Motion[]
十二、图像处理：
· Distance Transforms of Sampled Functions[]
· The Computer Vision Homepage[]
· Efficient appearance distances between windows[]
· Image Exploration algorithm[]
· Motion Magnification 运动放大 []
· Bilateral Filtering for Gray and Color Images 双边滤波器 []
· A Fast Approximation of the Bilateral Filter using a Signal Processing Approach [
十三、一些实用工具：
· EGT: a Toolbox for Multiple View Geometry and Visual Servoing[] []
· a development kit of matlab mex functions for OpenCV library[]
· Fast Artificial Neural Network Library[]
十四、人手及指尖检测与识别：
· finger-detection-and-gesture-recognition []
· Hand and Finger Detection using JavaCV[]
· Hand and fingers detection[]
十五、场景解释：
· Nonparametric Scene Parsing via Label Transfer []
十六、光流Optical flow：
· High accuracy optical flow using a theory for warping []
· Dense Trajectories Video Description []
· SIFT Flow: Dense Correspondence across Scenes and its Applications[]
· KLT: An Implementation of the Kanade-Lucas-Tomasi Feature Tracker []
· Tracking Cars Using Optical Flow[]
· Secrets of optical flow estimation and their principles[]
· implmentation of the Black and Anandan dense optical flow method[]
· Optical Flow Computation[]
· Beyond Pixels: Exploring New Representations and Applications for Motion Analysis[]
· A Database and Evaluation Methodology for Optical Flow[]
· optical flow relative[]
· Robust Optical Flow Estimation []
· optical flow[]
十七、图像检索Image Retrieval：
· Semi-Supervised Distance Metric Learning for Collaborative Image Retrieval ][]
十八、马尔科夫随机场Markov Random Fields：
· Markov Random Fields for Super-Resolution ]
· A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors []
十九、运动检测Motion detection：
· Moving Object Extraction, Using Models or Analysis of Regions ]
· Background Subtraction: Experiments and Improvements for ViBe []
· A Self-Organizing Approach to Background Subtraction for Visual Surveillance Applications []
· changedetection.net: A new change detection benchmark dataset[]
· ViBe - a powerful technique for background detection and subtraction in video sequences[]
· Background Subtraction Program[]
· Motion Detection Algorithms[]
· Stuttgart Artificial Background Subtraction Dataset[]
· Object Detection, Motion Estimation, and Tracking[]