计算机视觉与模式识别代码合集第二版two

Posted 2020-06-08

Topic	Name	Reference	code
Image Segmentation	Segmentation by Minimum Code Length	AY Yang, J. Wright, S. Shankar Sastry, Y. Ma , Unsupervised Segmentation of Natural Images via Lossy Data Compression, CVIU, 2007	code
Image Segmentation	Normalized Cut	J. Shi and J Malik, Normalized Cuts and Image Segmentation, PAMI, 2000	code
Image Segmentation	Entropy Rate Superpixel Segmentation	M.-Y. Liu, O. Tuzel, S. Ramalingam, and R. Chellappa, Entropy Rate Superpixel Segmentation, CVPR 2011	code
Image Segmentation	Mean-Shift Image Segmentation - EDISON	D. Comaniciu, P Meer. Mean Shift: A Robust Approach Toward Feature Space Analysis. PAMI 2002	code
Image Segmentation	Efficient Graph-based Image Segmentation - Matlab Wrapper	P. Felzenszwalb and D. Huttenlocher. Efficient Graph-Based Image Segmentation, IJCV 2004	code
Image Segmentation	Biased Normalized Cut	S. Maji, N. Vishnoi and J. Malik, Biased Normalized Cut, CVPR 2011	code
Image Segmentation	Multiscale Segmentation Tree	E. Akbas and N. Ahuja, “From ramp discontinuities to segmentation tree,” ACCV 2009 and N. Ahuja, “A Transform for Multiscale Image Segmentation by Integrated Edge and Region Detection,” PAMI 1996	code
Image Segmentation	Efficient Graph-based Image Segmentation - C++ code	P. Felzenszwalb and D. Huttenlocher. Efficient Graph-Based Image Segmentation, IJCV 2004	code
Image Segmentation	Superpixel by Gerg Mori	X. Ren and J. Malik. Learning a classification model for segmentation. ICCV, 2003	code
Image Segmentation	Segmenting Scenes by Matching Image Composites	B. Russell, AA Efros, J. Sivic, WT Freeman, A. Zisserman, NIPS 2009	code
Image Segmentation	Recovering Occlusion Boundaries from a Single Image	D. Hoiem, A. Stein, AA Efros, M. Hebert, Recovering Occlusion Boundaries from a Single Image, ICCV 2007.	code
Image Segmentation	Quick-Shift	A. Vedaldi and S. Soatto, Quick Shift and Kernel Methodsfor Mode Seeking, ECCV, 2008	code
Image Segmentation	SLIC Superpixels	R. Achanta, A. Shaji, K. Smith, A. Lucchi, P. Fua, and S. Susstrunk, SLIC Superpixels, EPFL Technical Report, 2010	code
Image Segmentation	Mean-Shift Image Segmentation - Matlab Wrapper	D. Comaniciu, P Meer. Mean Shift: A Robust Approach Toward Feature Space Analysis. PAMI 2002	code
Image Segmentation	OWT-UCM Hierarchical Segmentation	P. Arbelaez, M. Maire, C. Fowlkes and J. Malik. Contour Detection and Hierarchical Image Segmentation. PAMI, 2011	code
Image Segmentation	Turbepixels	A. Levinshtein, A. Stere, KN Kutulakos, DJ Fleet, SJ Dickinson, and K. Siddiqi, TurboPixels: Fast Superpixels Using Geometric Flows, PAMI 2009	code
Image Super-resolution	MRF for image super-resolution	W. T Freeman and C. Liu. Markov Random Fields for Super-resolution and Texture Synthesis. In A. Blake, P. Kohli, and C. Rother, eds., Advances in Markov Random Fields for Vision and Image Processing, Chapter 10. MIT Press, 2011
Image Super-resolution	Single-Image Super-Resolution Matlab Package	R. Zeyde, M. Elad, and M. Protter, On Single Image Scale-Up using Sparse-Representations, LNCS 2010	code
Image Super-resolution	Self-Similarities for Single Frame Super-Resolution	C.-Y. Yang, J.-B. Huang, and M.-H. Yang, Exploiting Self-Similarities for Single Frame Super-Resolution, ACCV 2010	code
Image Super-resolution	MDSP Resolution Enhancement Software	S. Farsiu, D. Robinson, M. Elad, and P. Milanfar, Fast and Robust Multi-frame Super-resolution, TIP 2004	code
Image Super-resolution	Sprarse coding super-resolution	J. Yang, J. Wright, TS Huang, and Y. Ma. Image super-resolution via sparse representation, TIP 2010	code
Image Super-resolution	Multi-frame image super-resolution	Pickup, LC Machine Learning in Multi-frame Image Super-resolution, PhD thesis	code
Image Understanding	SuperParsing	J. Tighe and S. Lazebnik, SuperParsing: Scalable Nonparametric Image Parsing with Superpixels, ECCV 2010	code
Image Understanding	Discriminative Models for Multi-Class Object Layout	C. Desai, D. Ramanan, C. Fowlkes. "Discriminative Models for Multi-Class Object Layout, IJCV 2011	code
Image Understanding	Nonparametric Scene Parsing via Label Transfer	C. Liu, J. Yuen, and Antonio Torralba, Nonparametric Scene Parsing via Label Transfer, PAMI 2011	code
Image Understanding	Blocks World Revisited: Image Understanding using Qualitative Geometry and Mechanics	A. Gupta, AA Efros, M. Hebert, Blocks World Revisited: Image Understanding using Qualitative Geometry and Mechanics, ECCV 2010	code
Image Understanding	Towards Total Scene Understanding	L.-J. Li, R. Socher and Li F.-F.. Towards Total Scene Understanding:Classification, Annotation and Segmentation in an Automatic Framework, CVPR 2009	code
Image Understanding	Object Bank	Li-Jia Li, Hao Su, Eric P. Xing and Li Fei-Fei. Object Bank: A High-Level Image Representation for Scene Classification and Semantic Feature Sparsification, NIPS 2010	code
Kernels and Distances	Fast Directional Chamfer Matching		code
Kernels and Distances	Efficient Earth Mover‘s Distance with L1 Ground Distance (EMD_L1)	H. Ling and K. Okada, An Efficient Earth Mover‘s Distance Algorithm for Robust Histogram Comparison, PAMI 2007	code
Kernels and Distances	Diffusion-based distance	H. Ling and K. Okada, Diffusion Distance for Histogram Comparison, CVPR 2006	code
Low-Rank Modeling	TILT: Transform Invariant Low-rank Textures	Z. Zhang, A. Ganesh, X. Liang, and Y. Ma, TILT: Transform Invariant Low-rank Textures, IJCV 2011	code
Low-Rank Modeling	Low-Rank Matrix Recovery and Completion		code
Low-Rank Modeling	RASL: Robust Batch Alignment of Images by Sparse and Low-Rank Decomposition	Y. Peng, A. Ganesh, J. Wright, W. Xu, and Y. Ma, RASL: Robust Batch Alignment of Images by Sparse and Low-Rank Decomposition, CVPR 2010	code
MRF Optimization	MRF Minimization Evaluation	R. Szeliski et al., A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors, PAMI, 2008	code
MRF Optimization	Max-flow/min-cut for shape fitting	V. Lempitsky and Y. Boykov, Global Optimization for Shape Fitting, CVPR 2007	code
MRF Optimization	Max-flow/min-cut	Y. Boykov and V. Kolmogorov, An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision, PAMI 2004	code
MRF Optimization	Planar Graph Cut	FR Schmidt, E. Toppe and D. Cremers, Ef?cient Planar Graph Cuts with Applications in Computer Vision, CVPR 2009	code
MRF Optimization	Max-flow/min-cut for massive grids	A. Delong and Y. Boykov, A Scalable Graph-Cut Algorithm for ND Grids, CVPR 2008	code
MRF Optimization	Multi-label optimization	Y. Boykov, O. Verksler, and R. Zabih, Fast Approximate Energy Minimization via Graph Cuts, PAMI 2001	code
Machine Learning	Statistical Pattern Recognition Toolbox	MI Schlesinger, V. Hlavac: Ten lectures on the statistical and structural pattern recognition, Kluwer Academic Publishers, 2002	code
Machine Learning	Netlab Neural Network Software	CM Bishop, Neural Networks for Pattern RecognitionㄝOxford University Press, 1995	code
Machine Learning	Boosting Resources by Liangliang Cao	http://www.ifp.illinois.edu/~cao4/reading/boostingbib.htm	code
Machine Learning	FastICA package for MATLAB	http://research.ics.tkk.fi/ica/book/	code
Multi-View Stereo	Patch-based Multi-view Stereo Software	Y. Furukawa and J. Ponce, Accurate, Dense, and Robust Multi-View Stereopsis, PAMI 2009	code

 

Topic	Name	Reference	code
Multi-View Stereo	Clustering Views for Multi-view Stereo	Y. Furukawa, B. Curless, SM Seitz, and R. Szeliski, Towards Internet-scale Multi-view Stereo, CVPR 2010	code
Multi-View Stereo	Multi-View Stereo Evaluation	S. Seitz et al. A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms, CVPR 2006	code
Multiple Instance Learning	DD-SVM	Yixin Chen and James Z. Wang, Image Categorization by Learning and Reasoning with Regions, JMLR 2004
Multiple Instance Learning	MIForests	C. Leistner, A. Saffari, and H. Bischof, MIForests: Multiple-Instance Learning with Randomized Trees, ECCV 2010	code
Multiple Instance Learning	MILIS	Z. Fu, A. Robles-Kelly, and J. Zhou, MILIS: Multiple instance learning with instance selection, PAMI 2010
Multiple Instance Learning	MILES	Y. Chen, J. Bi and JZ Wang, MILES: Multiple-Instance Learning via Embedded Instance Selection. PAMI 2006	code
Multiple Kernel Learning	SHOGUN	S. Sonnenburg, G. R?tsch, C. Sch?fer, B. Sch?lkopf . Large scale multiple kernel learning. JMLR, 2006	code
Multiple Kernel Learning	OpenKernel.org	F. Orabona and L. Jie. Ultra-fast optimization algorithm for sparse multi kernel learning. ICML, 2011	code
Multiple Kernel Learning	SimpleMKL	A. Rakotomamonjy, F. Bach, S. Canu, and Y. Grandvalet.Simplemkl. JMRL, 2008	code
Multiple Kernel Learning	DOGMA	F. Orabona, L. Jie, and B. Caputo. Online-batch strongly convex multi kernel learning. CVPR, 2010	code
Multiple View Geometry	MATLAB and Octave Functions for Computer Vision and Image Processing	PD Kovesi. MATLAB and Octave Functions for Computer Vision and Image Processing, http://www.csse.uwa.edu.au/~pk/research/matlabfns	code
Multiple View Geometry	Matlab Functions for Multiple View Geometry		code
Nearest Neighbors Matching	ANN: Approximate Nearest Neighbor Searching		code
Nearest Neighbors Matching	Spectral Hashing	Y. Weiss, A. Torralba, R. Fergus, Spectral Hashing, NIPS 2008	code
Nearest Neighbors Matching	Coherency Sensitive Hashing	S. Korman, S. Avidan, Coherency Sensitive Hashing, ICCV 2011	code
Nearest Neighbors Matching	FLANN: Fast Library for Approximate Nearest Neighbors		code
Nearest Neighbors Matching	LDAHash: Binary Descriptors for Matching in Large Image Databases	C. Strecha, AM Bronstein, MM Bronstein and P. Fua. LDAHash: Improved matching with smaller descriptors, PAMI, 2011.	code
Object Detection	Poselet	L. Bourdev, J. Malik, Poselets: Body Part Detectors Trained Using 3D Human Pose Annotations, ICCV 2009	code
Object Detection	Cascade Object Detection with Deformable Part Models	P. Felzenszwalb, R. Girshick, D. McAllester. Cascade Object Detection with Deformable Part Models. CVPR, 2010	code
Object Detection	Multiple Kernels	A. Vedaldi, V. Gulshan, M. Varma, and A. Zisserman, Multiple Kernels for Object Detection. ICCV, 2009	code
Object Detection	Hough Forests for Object Detection	J. Gall and V. Lempitsky, Class-Speci?c Hough Forests for Object Detection, CVPR, 2009	code
Object Detection	Discriminatively Trained Deformable Part Models	P. Felzenszwalb, R. Girshick, D. McAllester, D. Ramanan. Object Detection with Discriminatively Trained Part Based Models, PAMI, 2010	code
Feature Extraction andObject Detection	Histogram of Oriented Graidents - OLT for windows	N. Dalal and B. Triggs. Histograms of Oriented Gradients for Human Detection. CVPR 2005	code
Feature Extraction andObject Detection	Histogram of Oriented Graidents - INRIA Object Localization Toolkit	N. Dalal and B. Triggs. Histograms of Oriented Gradients for Human Detection. CVPR 2005	code
Object Detection	Recognition using regions	C. Gu, JJ Lim, P. Arbelaez, and J. Malik, CVPR 2009	code
Object Detection	A simple parts and structure object detector	ICCV 2005 short courses on Recognizing and Learning Object Categories	code
Object Detection	Feature Combination	P. Gehler and S. Nowozin, On Feature Combination for Multiclass Object Detection, ICCV, 2009	code
Object Detection	Ensemble of Exemplar-SVMs	T. Malisiewicz, A. Gupta, A. Efros. Ensemble of Exemplar-SVMs for Object Detection and Beyond . ICCV, 2011	code
Object Detection	A simple object detector with boosting	ICCV 2005 short courses on Recognizing and Learning Object Categories	code
Object Detection	Max-Margin Hough Transform	S. Maji and J. Malik, Object Detection Using a Max-Margin Hough Transform. CVPR 2009	code
Object Detection	Implicit Shape Model	B. Leibe, A. Leonardis, B. Schiele. Robust Object Detection with Interleaved Categorization and Segmentation, IJCV, 2008	code
Object Detection	Ensemble of Exemplar-SVMs for Object Detection and Beyond	T. Malisiewicz, A. Gupta, AA Efros, Ensemble of Exemplar-SVMs for Object Detection and Beyond , ICCV 2011	code
Object Detection	Viola-Jones Object Detection	P. Viola and M. Jones, Rapid Object Detection Using a Boosted Cascade of Simple Features, CVPR, 2001	code
Object Discovery	Using Multiple Segmentations to Discover Objects and their Extent in Image Collections	B. Russell, AA Efros, J. Sivic, WT Freeman, A. Zisserman, Using Multiple Segmentations to Discover Objects and their Extent in Image Collections, CVPR 2006	code
Object Proposal	Objectness measure	B. Alexe, T. Deselaers, V. Ferrari, What is an Object?, CVPR 2010	code
Object Proposal	Parametric min-cut	J. Carreira and C. Sminchisescu. Constrained Parametric Min-Cuts for Automatic Object Segmentation, CVPR 2010	code
Object Proposal	Region-based Object Proposal	I. Endres and D. Hoiem. Category Independent Object Proposals, ECCV 2010	code
Object Recognition	Recognition by Association via Learning Per-exemplar Distances	T. Malisiewicz, AA Efros, Recognition by Association via Learning Per-exemplar Distances, CVPR 2008	code
Object Recognition	Biologically motivated object recognition	T. Serre, L. Wolf and T. Poggio. Object recognition with features inspired by visual cortex, CVPR 2005	code
Object Segmentation	Geodesic Star Convexity for Interactive Image Segmentation	V. Gulshan, C. Rother, A. Criminisi, A. Blake and A. Zisserman.Geodesic star convexity for interactive image segmentation	code
Object Segmentation	ClassCut for Unsupervised Class Segmentation	B. Alexe, T. Deselaers and V. Ferrari, ClassCut for Unsupervised Class Segmentation, ECCV 2010	code
Object Segmentation	Sparse to Dense Labeling	P. Ochs, T. Brox, Object Segmentation in Video: A Hierarchical Variational Approach for Turning Point Trajectories into Dense Regions, ICCV 2011	code
Optical Flow	Optical Flow by Deqing Sun	D. Sun, S. Roth, MJ Black, Secrets of Optical Flow Estimation and Their Principles, CVPR, 2010	code
Optical Flow	Classical Variational Optical Flow	T. Brox, A. Bruhn, N. Papenberg, J. Weickert, High accuracy optical flow estimation based on a theory for warping, ECCV 2004	code
Optical Flow	Large Displacement Optical Flow	T. Brox, J. Malik, Large displacement optical flow: descriptor matching in variational motion estimation, PAMI 2011	code
Optical Flow	Dense Point Tracking	N. Sundaram, T. Brox, K. Keutzer Dense point trajectories by GPU-accelerated large displacement optical flow, ECCV 2010	code
Optical Flow	Optical Flow Evaluation	S. Baker et al. A Database and Evaluation Methodology for Optical Flow, IJCV, 2011	code

待续：计算机视觉与模式识别代码合集第二版three