引自：http://cvchina.net/post/50.html
一、特征提取Feature Extraction：
-
SIFT [1] [Demo program][SIFT Library] [VLFeat]
-
PCA-SIFT [2] [Project]
-
Affine-SIFT [3] [Project]
-
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]
-
Histogram of Oriented Graidents [10] [INRIA Object Localization Toolkit] [OLT toolkit for Windows]
-
GIST [11] [Project]
-
Shape Context [12] [Project]
-
Color Descriptor [13] [Project]
-
Pyramids of Histograms of Oriented Gradients [Code]
-
Boundary Preserving Dense Local Regions [15][Project]
-
Weighted Histogram[Code]
-
An OpenCV - C++ implementation of Local Self Similarity Descriptors [Project]
-
Fast Sparse Representation with Prototypes[Project]
-
Corner Detection [Project]
-
AGAST Corner Detector: faster than FAST and even FAST-ER[Project]
-
Real-time Facial Feature Detection using Conditional Regression Forests[Project]
-
Global and Efficient Self-Similarity for Object Classification and Detection[code]
-
WαSH: Weighted α-Shapes for Local Feature Detection[Project]
-
HOG[Project]
-
Online Selection of Discriminative Tracking Features[Project]
二、图像分割Image Segmentation：
-
Normalized Cut [1] [Matlab code]
-
Gerg Mori’ Superpixel code [2] [Matlab code]
-
Efficient Graph-based Image Segmentation [3] [C++ code] [Matlab wrapper]
-
Mean-Shift Image Segmentation [4] [EDISON C++ code] [Matlab wrapper]
-
OWT-UCM Hierarchical Segmentation [5] [Resources]
-
Turbepixels [6] [Matlab code 32bit] [Matlab code 64bit] [Updated code]
-
Quick-Shift [7] [VLFeat]
-
SLIC Superpixels [8] [Project]
-
Segmentation by Minimum Code Length [9] [Project]
-
Biased Normalized Cut [10] [Project]
-
Segmentation Tree [11-12] [Project]
-
Entropy Rate Superpixel Segmentation [13] [Code]
-
Fast Approximate Energy Minimization via Graph Cuts[Paper][Code]
-
Efficient Planar Graph Cuts with Applications in Computer Vision[Paper][Code]
-
Isoperimetric Graph Partitioning for Image Segmentation[Paper][Code]
-
Blossom V: A new implementation of a minimum cost perfect matching algorithm[Code]
-
An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Computer Vision[Paper][Code]
-
Geodesic Star Convexity for Interactive Image Segmentation[Project]
-
Contour Detection and Image Segmentation Resources[Project][Code]
-
Biased Normalized Cuts[Project]
-
Max-flow/min-cut[Project]
-
Chan-Vese Segmentation using Level Set[Project]
-
A Toolbox of Level Set Methods[Project]
-
Re-initialization Free Level Set Evolution via Reaction Diffusion[Project]
-
A Variational Multiphase Level Set Approach to Simultaneous Segmentation and Bias Correction[Paper][Code]
-
Level Set Method Research by Chunming Li[Project]
-
ClassCut for Unsupervised Class Segmentation[code]
-
SEEDS: Superpixels Extracted via Energy-Driven Sampling [Project][other]
三、目标检测Object Detection：
-
A simple object detector with boosting [Project]
-
INRIA Object Detection and Localization Toolkit [1] [Project]
-
Discriminatively Trained Deformable Part Models [2] [Project]
-
Cascade Object Detection with Deformable Part Models [3] [Project]
-
Poselet [4] [Project]
-
Implicit Shape Model [5] [Project]
-
Viola and Jones’s Face Detection [6] [Project]
-
Bayesian Modelling of Dyanmic Scenes for Object Detection[Paper][Code]
-
Hand detection using multiple proposals[Project]
-
Color Constancy, Intrinsic Images, and Shape Estimation[Paper][Code]
-
Discriminatively trained deformable part models[Project]
-
Gradient Response Maps for Real-Time Detection of Texture-Less Objects: LineMOD [Project]
-
Image Processing On Line[Project]
-
Robust Optical Flow Estimation[Project]
-
Where's Waldo: Matching People in Images of Crowds[Project]
-
Scalable Multi-class Object Detection[Project]
-
Class-Specific Hough Forests for Object Detection[Project]
-
Deformed Lattice Detection In Real-World Images[Project]
-
Discriminatively trained deformable part models[Project]
四、显著性检测Saliency Detection：
-
Itti, Koch, and Niebur’ saliency detection [1] [Matlab code]
-
Frequency-tuned salient region detection [2] [Project]
-
Saliency detection using maximum symmetric surround [3] [Project]
-
Attention via Information Maximization [4] [Matlab code]
-
Context-aware saliency detection [5] [Matlab code]
-
Graph-based visual saliency [6] [Matlab code]
-
Saliency detection: A spectral residual approach. [7] [Matlab code]
-
Segmenting salient objects from images and videos. [8] [Matlab code]
-
Saliency Using Natural statistics. [9] [Matlab code]
-
Discriminant Saliency for Visual Recognition from Cluttered Scenes. [10] [Code]
-
Learning to Predict Where Humans Look [11] [Project]
-
Global Contrast based Salient Region Detection [12] [Project]
-
Bayesian Saliency via Low and Mid Level Cues[Project]
-
Top-Down Visual Saliency via Joint CRF and Dictionary Learning[Paper][Code]
-
Saliency Detection: A Spectral Residual Approach[Code]
五、图像分类、聚类Image Classification, Clustering
-
Pyramid Match [1] [Project]
-
Spatial Pyramid Matching [2] [Code]
-
Locality-constrained Linear Coding [3] [Project] [Matlab code]
-
Sparse Coding [4] [Project] [Matlab code]
-
Texture Classification [5] [Project]
-
Multiple Kernels for Image Classification [6] [Project]
-
Feature Combination [7] [Project]
-
SuperParsing [Code]
-
Large Scale Correlation Clustering Optimization[Matlab code]
-
Detecting and Sketching the Common[Project]
-
User Assisted Separation of Reflections from a Single Image Using a Sparsity Prior[Paper][Code]
-
Filters for Texture Classification[Project]
-
Multiple Kernel Learning for Image Classification[Project]
-
SLIC Superpixels[Project]
六、抠图Image Matting
-
A Closed Form Solution to Natural Image Matting [Code]
-
Spectral Matting [Project]
-
Learning-based Matting [Code]
七、目标跟踪Object Tracking：
-
A Forest of Sensors - Tracking Adaptive Background Mixture Models [Project]
-
Object Tracking via Partial Least Squares Analysis[Paper][Code]
-
Robust Object Tracking with Online Multiple Instance Learning[Paper][Code]
-
Online Visual Tracking with Histograms and Articulating Blocks[Project]
-
Incremental Learning for Robust Visual Tracking[Project]
-
Real-time Compressive Tracking[Project]
-
Robust Object Tracking via Sparsity-based Collaborative Model[Project]
-
Visual Tracking via Adaptive Structural Local Sparse Appearance Model[Project]
-
Online Discriminative Object Tracking with Local Sparse Representation[Paper][Code]
-
Superpixel Tracking[Project]
-
Learning Hierarchical Image Representation with Sparsity, Saliency and Locality[Paper][Code]
-
Visual Tracking with Online Multiple Instance Learning[Project]
-
Object detection and recognition[Project]
-
Compressive Sensing Resources[Project]
-
Robust Real-Time Visual Tracking using Pixel-Wise Posteriors[Project]
-
Tracking-Learning-Detection[Project][OpenTLD/C++ Code]
-
the HandVu：vision-based hand gesture interface[Project]
-
Learning Probabilistic Non-Linear Latent Variable Models for Tracking Complex Activities[Project]
八、Kinect：
九、3D相关：
-
Shape From Shading Using Linear Approximation[Code]
-
Combining Shape from Shading and Stereo Depth Maps[Project][Code]
-
A Spatio-Temporal Descriptor based on 3D Gradients (HOG3D)[Project][Code]
-
Multi-camera Scene Reconstruction via Graph Cuts[Paper][Code]
-
A Fast Marching Formulation of Perspective Shape from Shading under Frontal Illumination[Paper][Code]
-
Reconstruction:3D Shape, Illumination, Shading, Reflectance, Texture[Project]
-
Monocular Tracking of 3D Human Motion with a Coordinated Mixture of Factor Analyzers[Code]
-
Learning 3-D Scene Structure from a Single Still Image[Project]
十、机器学习算法：
-
Matlab class for computing Approximate Nearest Nieghbor (ANN) [Matlab class providing interface toANN library]
-
Random Sampling[code]
-
Probabilistic Latent Semantic Analysis (pLSA)[Code]
-
FASTANN and FASTCLUSTER for approximate k-means (AKM)[Project]
-
Fast Intersection / Additive Kernel SVMs[Project]
-
SVM[Code]
-
Ensemble learning[Project]
-
Deep Learning[Net]
-
Deep Learning Methods for Vision[Project]
-
Neural Network for Recognition of Handwritten Digits[Project]
-
Training a deep autoencoder or a classifier on MNIST digits[Project]
-
THE MNIST DATABASE of handwritten digits[Project]
-
Ersatz：deep neural networks in the cloud[Project]
-
Deep Learning [Project]
-
sparseLM : Sparse Levenberg-Marquardt nonlinear least squares in C/C++[Project]
-
Weka 3: Data Mining Software in Java[Project]
-
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]
-
Training a deep autoencoder or a classifier on MNIST digits[Project]
-
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]
-
Sparse coding simulation software[Project]
-
Visual Recognition and Machine Learning Summer School[Software]
十一、目标、行为识别Object, Action Recognition：
-
Action Recognition Using a Distributed Representation of Pose and Appearance[Project]
-
2D Articulated Human Pose Estimation[Project]
-
Fast Human Pose Estimation Using Appearance and Motion via Multi-Dimensional Boosting Regression[Paper][Code]
-
Quasi-dense wide baseline matching[Project]
-
ChaLearn Gesture Challenge: Principal motion: PCA-based reconstruction of motion histograms[Project]
-
Real Time Head Pose Estimation with Random Regression Forests[Project]
-
2D Action Recognition Serves 3D Human Pose Estimation[Project]
-
A Hough Transform-Based Voting Framework for Action Recognition[Project]
-
Motion Interchange Patterns for Action Recognition in Unconstrained Videos[Project]
-
2D articulated human pose estimation software[Project]
-
Learning and detecting shape models [code]
-
Progressive Search Space Reduction for Human Pose Estimation[Project]
-
Learning Non-Rigid 3D Shape from 2D Motion[Project]
十二、图像处理：
-
Distance Transforms of Sampled Functions[Project]
-
The Computer Vision Homepage[Project]
-
Efficient appearance distances between windows[code]
-
Image Exploration algorithm[code]
-
Motion Magnification 运动放大 [Project]
-
Bilateral Filtering for Gray and Color Images 双边滤波器 [Project]
-
A Fast Approximation of the Bilateral Filter using a Signal Processing Approach [Project]
十三、一些实用工具：
-
EGT: a Toolbox for Multiple View Geometry and Visual Servoing[Project] [Code]
-
a development kit of matlab mex functions for OpenCV library[Project]
-
Fast Artificial Neural Network Library[Project]
十四、人手及指尖检测与识别：
-
finger-detection-and-gesture-recognition [Code]
-
Hand and Finger Detection using JavaCV[Project]
-
Hand and fingers detection[Code]
十五、场景解释：
-
Nonparametric Scene Parsing via Label Transfer [Project]
十六、光流Optical flow：
-
High accuracy optical flow using a theory for warping [Project]
-
Dense Trajectories Video Description [Project]
-
SIFT Flow: Dense Correspondence across Scenes and its Applications[Project]
-
KLT: An Implementation of the Kanade-Lucas-Tomasi Feature Tracker [Project]
-
Tracking Cars Using Optical Flow[Project]
-
Secrets of optical flow estimation and their principles[Project]
-
implmentation of the Black and Anandan dense optical flow method[Project]
-
Optical Flow Computation[Project]
-
Beyond Pixels: Exploring New Representations and Applications for Motion Analysis[Project]
-
A Database and Evaluation Methodology for Optical Flow[Project]
-
optical flow relative[Project]
-
Robust Optical Flow Estimation [Project]
-
optical flow[Project]
十七、图像检索Image Retrieval：
十八、马尔科夫随机场Markov Random Fields：
-
A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors [Project]
十九、运动检测Motion detection：
-
Moving Object Extraction, Using Models or Analysis of Regions [Project]
-
Background Subtraction: Experiments and Improvements for ViBe [Project]
-
A Self-Organizing Approach to Background Subtraction for Visual Surveillance Applications [Project]
-
changedetection.net: A new change detection benchmark dataset[Project]
-
ViBe - a powerful technique for background detection and subtraction in video sequences[Project]
-
Background Subtraction Program[Project]
-
Motion Detection Algorithms[Project]
-
Stuttgart Artificial Background Subtraction Dataset[Project]
-
Object Detection, Motion Estimation, and Tracking[Project]