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  • 计算机视觉与模式识别代码合集第二版three

    计算机视觉与模式识别代码合集第二版three

       

    Topic

    Name

    Reference

    code

    Optical Flow

    Horn and Schunck's Optical Flow

    		  

    code

    Optical Flow

    Black and Anandan's Optical Flow

    		  

    code

    Pose Estimation

    Training Deformable Models for Localization

    Ramanan, D. "Learning to Parse Images of Articulated Bodies."NIPS 2006

    code

    Pose Estimation

    Calvin Upper-Body Detector

    E. Marcin, F. Vittorio, Better Appearance Models for Pictorial Structures, BMVC 2009

    code

    Pose Estimation

    Articulated Pose Estimation using Flexible Mixtures of Parts

    Y. Yang, D. Ramanan, Articulated Pose Estimation using Flexible Mixtures of Parts, CVPR 2011

    code

    Pose Estimation

    Estimating Human Pose from Occluded Images

    J.-B. Huang and M.-H. Yang, Estimating Human Pose from Occluded Images, ACCV 2009

    code

    Saliency Detection

    Saliency detection: A spectral residual approach

    X. Hou and L. Zhang. Saliency detection: A spectral residual approach. CVPR, 2007

    code

    Saliency Detection

    Saliency Using Natural statistics

    L. Zhang, M. Tong, T. Marks, H. Shan, and G. Cottrell. Sun: A bayesian framework for saliency using natural statistics. Journal of Vision, 2008

    code

    Saliency Detection

    Attention via Information Maximization

    N. Bruce and J. Tsotsos. Saliency based on information maximization. In NIPS, 2005

    code

    Saliency Detection

    Itti, Koch, and Niebur' saliency detection

    L. Itti, C. Koch, and E. Niebur. A model of saliency-based visual attention for rapid scene analysis. PAMI, 1998

    code

    Saliency Detection

    Frequency-tuned salient region detection

    R. Achanta, S. Hemami, F. Estrada, and S. Susstrunk.Frequency-tuned salient region detection. In CVPR, 2009

    code

    Saliency Detection

    Saliency-based video segmentation

    K. Fukuchi, K. Miyazato, A. Kimura, S. Takagi and J. Yamato, Saliency-based video segmentation with graph cuts and sequentially updated priors, ICME 2009

    code

    Saliency Detection

    Segmenting salient objects from images and videos

    E. Rahtu, J. Kannala, M. Salo, and J. Heikkila. Segmenting salient objects from images and videos. CVPR, 2010

    code

    Saliency Detection

    Graph-based visual saliency

    J. Harel, C. Koch, and P. Perona. Graph-based visual saliency.NIPS, 2007

    code

    Saliency Detection

    Learning to Predict Where Humans Look

    T. Judd and K. Ehinger and F. Durand and A. Torralba, Learning to Predict Where Humans Look, ICCV, 2009

    code

    Saliency Detection

    Spectrum Scale Space based Visual Saliency

    J Li, M D. Levine, X An and H. He, Saliency Detection Based on Frequency and Spatial Domain Analyses, BMVC 2011

    code

    Saliency Detection

    Discriminant Saliency for Visual Recognition from Cluttered Scenes

    D. Gao and N. Vasconcelos, Discriminant Saliency for Visual Recognition from Cluttered Scenes, NIPS, 2004

    code

    Saliency Detection

    Context-aware saliency detection

    S. Goferman, L. Zelnik-Manor, and A. Tal. Context-aware saliency detection. In CVPR, 2010.

    code

    Saliency Detection

    Saliency detection using maximum symmetric surround

    R. Achanta and S. Susstrunk. Saliency detection using maximum symmetric surround. In ICIP, 2010

    code

    Saliency Detection

    Global Contrast based Salient Region Detection

    M.-M. Cheng, G.-X. Zhang, NJ Mitra, X. Huang, S.-M. Hu. Global Contrast based Salient Region Detection. CVPR, 2011

    code

    Saliency Detection

    Learning Hierarchical Image Representation with Sparsity, Saliency and Locality

    J. Yang and M.-H. Yang, Learning Hierarchical Image Representation with Sparsity, Saliency and Locality, BMVC 2011

    		  

    Sparse Representation

    Centralized Sparse Representation for Image Restoration

    W. Dong, L. Zhang and G. Shi, “Centralized Sparse Representation for Image Restoration,” ICCV 2011

    code

    Sparse Representation

    Efficient sparse coding algorithms

    H. Lee, A. Battle, R. Rajat and AY Ng, Efficient sparse coding algorithms, NIPS 2007

    code

    Sparse Representation

    Fisher Discrimination Dictionary Learning for Sparse Representation

    M. Yang, L. Zhang, X. Feng and D. Zhang, Fisher Discrimination Dictionary Learning for Sparse Representation, ICCV 2011

    code

    Sparse Representation

    Robust Sparse Coding for Face Recognition

    M. Yang, L. Zhang, J. Yang and D. Zhang, “Robust Sparse Coding for Face Recognition,” CVPR 2011

    code

    Sparse Representation

    Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing

    M. Elad, Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing

    code

    Sparse Representation

    SPArse Modeling Software

    J. Mairal, F. Bach, J. Ponce and G. Sapiro. Online Learning for Matrix Factorization and Sparse Coding, JMLR 2010

    code

    Sparse Representation

    Sparse coding simulation software

    Olshausen BA, Field DJ, "Emergence of Simple-Cell Receptive Field Properties by Learning a Sparse Code for Natural Images", Nature 1996

    code

    Sparse Representation

    A Linear Subspace Learning Approach via Sparse Coding

    L. Zhang, P. Zhu, Q. Hu and D. Zhang, “A Linear Subspace Learning Approach via Sparse Coding,” ICCV 2011

    code

    Stereo

    Constant-Space Belief Propagation

    Q. Yang, L. Wang, and N. Ahuja, A Constant-Space Belief Propagation Algorithm for Stereo Matching, CVPR 2010

    code

    Stereo

    Stereo Evaluation

    D. Scharstein and R. Szeliski. A taxonomy and evaluation of dense two-frame stereo correspondence algorithms, IJCV 2001

    code

    Image Denoising andStereo Matching

    Efficient Belief Propagation for Early Vision

    PF Felzenszwalb and DP Huttenlocher, Efficient Belief Propagation for Early Vision, IJCV, 2006

    code

    Structure from motion

    Nonrigid Structure From Motion in Trajectory Space

    		  

    code

    Structure from motion

    libmv

    		  

    code

    Structure from motion

    Bundler

    N. Snavely, S M. Seitz, R Szeliski. Photo Tourism: Exploring image collections in 3D. SIGGRAPH 2006

    code

    Structure from motion

    FIT3D

    		  

    code

    Structure from motion

    VisualSFM : A Visual Structure from Motion System

    		  

    code

    Structure from motion

    OpenSourcePhotogrammetry

    		  

    code

    Structure from motion

    Structure and Motion Toolkit in Matlab

    		  

    code

    Structure from motion

    Structure from Motion toolbox for Matlab by Vincent Rabaud

    		  

    code

    Subspace Learning

    Generalized Principal Component Analysis

    R. Vidal, Y. Ma and S. Sastry. Generalized Principal Component Analysis (GPCA), CVPR 2003

    code

    Text Recognition

    Text recognition in the wild

    K. Wang, B. Babenko, and S. Belongie, End-to-end Scene Text Recognition, ICCV 2011

    code

    Text Recognition

    Neocognitron for handwritten digit recognition

    K. Fukushima: "Neocognitron for handwritten digit recognition", Neurocomputing, 2003

    code

    Texture Synthesis

    Image Quilting for Texture Synthesis and Transfer

    AA Efros and WT Freeman, Image Quilting for Texture Synthesis and Transfer, SIGGRAPH 2001

    code

    Topic

    Name

    Reference

    code

    Visual Tracking

    GPU Implementation of Kanade-Lucas-Tomasi Feature Tracker

    S. N Sinha, J.-M. Frahm, M. Pollefeys and Y. Genc, Feature Tracking and Matching in Video Using Programmable Graphics Hardware, MVA, 2007

    code

    Visual Tracking

    Superpixel Tracking

    S. Wang, H. Lu, F. Yang, and M.-H. Yang, Superpixel Tracking, ICCV 2011

    code

    Visual Tracking

    Tracking with Online Multiple Instance Learning

    B. Babenko, M.-H. Yang, S. Belongie, Visual Tracking with Online Multiple Instance Learning, PAMI 2011

    code

    Visual Tracking

    Motion Tracking in Image Sequences

    C. Stauffer and WEL Grimson. Learning patterns of activity using real-time tracking, PAMI, 2000

    code

    Visual Tracking

    L1 Tracking

    X. Mei and H. Ling, Robust Visual Tracking using L1 Minimization, ICCV, 2009

    code

    Visual Tracking

    Online Discriminative Object Tracking with Local Sparse Representation

    Q. Wang, F. Chen, W. Xu, and M.-H. Yang, Online Discriminative Object Tracking with Local Sparse Representation, WACV 2012

    code

    Visual Tracking

    KLT: An Implementation of the Kanade-Lucas-Tomasi Feature Tracker

    BD Lucas and T. Kanade. An Iterative Image Registration Technique with an Application to Stereo Vision. IJCAI, 1981

    code

    Visual Tracking

    Online boosting trackers

    H. Grabner, and H. Bischof, On-line Boosting and Vision, CVPR, 2006

    code

    Visual Tracking

    Visual Tracking Decomposition

    J Kwon and KM Lee, Visual Tracking Decomposition, CVPR 2010

    code

    Visual Tracking

    Globally-Optimal Greedy Algorithms for Tracking a Variable Number of Objects

    H. Pirsiavash, D. Ramanan, C. Fowlkes. "Globally-Optimal Greedy Algorithms for Tracking a Variable Number of Objects, CVPR 2011

    code

    Visual Tracking

    Lucas-Kanade affine template tracking

    S. Baker and I. Matthews, Lucas-Kanade 20 Years On: A Unifying Framework, IJCV 2002

    code

    Visual Tracking

    Object Tracking

    A. Yilmaz, O. Javed and M. Shah, Object Tracking: A Survey, ACM Journal of Computing Surveys, Vol. 38, No. 4, 2006

    code

    Visual Tracking

    Visual Tracking with Histograms and Articulating Blocks

    SM Shshed Nejhum, J. Ho, and M.-H.Yang, Visual Tracking with Histograms and Articulating Blocks, CVPR 2008

    code

    Visual Tracking

    Tracking using Pixel-Wise Posteriors

    C. Bibby and I. Reid, Tracking using Pixel-Wise Posteriors, ECCV 2008

    code

    Visual Tracking

    Incremental Learning for Robust Visual Tracking

    D. Ross, J. Lim, R.-S. Lin, M.-H. Yang, Incremental Learning for Robust Visual Tracking, IJCV 2007

    code

    Visual Tracking

    Particle Filter Object Tracking

    		  

    code

    一共248篇。one：47、two：45、three： 49、four： 47、five： 44、six： 16。
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  • 原文地址：https://www.cnblogs.com/timssd/p/5155171.html
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