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

05-11 07:44