本文共 12193 字，大约阅读时间需要 40 分钟。

2013 ICCV

计算机视觉顶级会议和期刊

一、会议

顶级：

ICCV：International Conference on Computer Vision，国际计算机视觉大会

CVPR：International Conference on Computer Vision and Pattern Recognition，国际计算机视觉与模式识别大会

ECCV：European Conference on Computer Vision，欧洲计算机视觉大会

较好：

ICIP：International Conference on Image Processing，国际图像处理大会

BMVC：British Machine Vision Conference，英国机器视觉大会

ICPR：International Conference on Pattern Recognition，国际模式识别大会

ACCV：Asian Conference on Computer Vision，亚洲计算机视觉大会

二、期刊

顶级：

PAMI：IEEE Transactions on Pattern Analysis and Machine Intelligence，IEEE 模式分析与机器智能杂志

IJCV：International Journal on Computer Vision，国际计算机视觉杂志

较好：

CVIU：Computer Vision and Image Understanding，计算机视觉与图像理解

PR：Pattern Recognition，模式识别

PRL：Pattern Recognition Letters，模式识别快报

 

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[]

转载：