BCDEFGHIJKLMNOPQRSTU
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labeltopictyperesource_url:urlreference
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Scale-invariant feature transform (SIFT) - Demo SoftwareFeature Detection; Feature ExtractionCodehttp://www.cs.ubc.ca/~lowe/keypoints/D. Lowe. Distinctive Image Features from Scale-Invariant Keypoints, IJCV 2004.
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Scale-invariant feature transform (SIFT) - LibraryFeature Detection; Feature ExtractionCodehttp://blogs.oregonstate.edu/hess/code/sift/D. Lowe. Distinctive Image Features from Scale-Invariant Keypoints, IJCV 2004.
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Scale-invariant feature transform (SIFT) - VLFeatFeature Detection; Feature ExtractionCodehttp://www.vlfeat.org/D. Lowe. Distinctive Image Features from Scale-Invariant Keypoints, IJCV 2004.
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Normalized CutImage SegmentationCodehttp://www.cis.upenn.edu/~jshi/software/J. Shi and J Malik, Normalized Cuts and Image Segmentation, PAMI, 2000
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Discriminatively Trained Deformable Part ModelsObject DetectionCodehttp://people.cs.uchicago.edu/~pff/latent/P. Felzenszwalb, R. Girshick, D. McAllester, D. Ramanan.
Object Detection with Discriminatively Trained Part Based Models, PAMI, 2010
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PCA-SIFTFeature ExtractionCodehttp://www.cs.cmu.edu/~yke/pcasift/Y. Ke and R. Sukthankar, PCA-SIFT: A More Distinctive Representation for Local Image Descriptors,CVPR, 2004
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Affine-SIFTFeature Detection; Feature ExtractionCodehttp://www.ipol.im/pub/algo/my_affine_sift/J.M. Morel and G.Yu, ASIFT, A new framework for fully affine invariant image comparison. SIAM Journal on Imaging Sciences, 2009
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Speeded Up Robust Feature (SURF) - Open SURFFeature Detection; Feature ExtractionCodehttp://www.chrisevansdev.com/computer-vision-opensurf.htmlH. Bay, T. Tuytelaars and L. V. Gool SURF: Speeded Up Robust Features, ECCV, 2006
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Speeded Up Robust Feature (SURF) - Matlab WrapperFeature Detection; Feature ExtractionCodehttp://www.maths.lth.se/matematiklth/personal/petter/surfmex.phpH. Bay, T. Tuytelaars and L. V. Gool SURF: Speeded Up Robust Features, ECCV, 2006
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Maximally stable extremal regions (MSER)Feature Detection; Feature ExtractionCodehttp://www.robots.ox.ac.uk/~vgg/research/affine/J. Matas, O. Chum, M. Urba, and T. Pajdla. Robust wide baseline stereo from maximally stable extremal regions. BMVC, 2002
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Maximally stable extremal regions (MSER) - VLFeatFeature Detection; Feature ExtractionCodehttp://www.vlfeat.org/J. Matas, O. Chum, M. Urba, and T. Pajdla. Robust wide baseline stereo from maximally stable extremal regions. BMVC, 2002
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Geometric BlurFeature Detection; Feature ExtractionCodehttp://www.robots.ox.ac.uk/~vgg/software/MKL/A. C. Berg, T. L. Berg, and J. Malik. Shape matching and object recognition using low distortion correspondences. CVPR, 2005
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Local Self-Similarity DescriptorFeature ExtractionCodehttp://www.robots.ox.ac.uk/~vgg/software/SelfSimilarity/E. Shechtman and M. Irani. Matching local self-similarities across images and videos, CVPR, 2007
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Global and Efficient Self-SimilarityFeature ExtractionCodehttp://www.vision.ee.ethz.ch/~calvin/gss/selfsim_release1.0.tgzT. Deselaers and V. Ferrari. Global and Efficient Self-Similarity for Object Classification and Detection. CVPR 2010
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Histogram of Oriented Graidents - INRIA Object Localization ToolkitFeature Extraction; Object DetectionCodehttp://www.navneetdalal.com/softwareN. Dalal and B. Triggs. Histograms of Oriented Gradients for Human Detection. CVPR 2005
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Histogram of Oriented Graidents - OLT for windowsFeature Extraction; Object DetectionCodehttp://www.computing.edu.au/~12482661/hog.htmlN. Dalal and B. Triggs. Histograms of Oriented Gradients for Human Detection. CVPR 2005
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GIST DescriptorFeature ExtractionCodehttp://people.csail.mit.edu/torralba/code/spatialenvelope/A. Oliva and A. Torralba. Modeling the shape of the scene: a holistic representation of the spatial envelope, IJCV, 2001
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Shape ContextFeature ExtractionCodehttp://www.eecs.berkeley.edu/Research/Projects/CS/vision/shape/sc_digits.htmlS. Belongie, J. Malik and J. Puzicha. Shape matching and object recognition using shape contexts, PAMI, 2002
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Color DescriptorFeature Detection; Feature ExtractionCodehttp://koen.me/research/colordescriptors/K. E. A. van de Sande, T. Gevers and Cees G. M. Snoek, Evaluating Color Descriptors for Object and Scene Recognition, PAMI, 2010
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Pyramids of Histograms of Oriented Gradients (PHOG)Feature ExtractionCodehttp://www.robots.ox.ac.uk/~vgg/research/caltech/phog/phog.zipA. Bosch, A. Zisserman, and X. Munoz, Representing shape with a spatial pyramid kernel, CIVR, 2007
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Space-Time Interest Points (STIP) Feature Detection; Feature ExtractionCodehttp://www.irisa.fr/vista/Equipe/People/Laptev/download/stip-1.1-winlinux.zipI. Laptev, On Space-Time Interest Points, IJCV, 2005
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Boundary Preserving Dense Local RegionsFeature DetectionCodehttp://vision.cs.utexas.edu/projects/bplr/bplr.htmlJ. Kim and K. Grauman, Boundary Preserving Dense Local Regions, CVPR 2011
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Canny Edge DetectionFeature DetectionCodehttp://www.mathworks.com/help/toolbox/images/ref/edge.htmlJ. Canny, A Computational Approach To Edge Detection, PAMI, 1986
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FAST Corner DetectionFeature DetectionCodehttp://www.edwardrosten.com/work/fast.htmlE. Rosten and T. Drummond, Machine learning for high-speed corner detection, ECCV, 2006
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Affine Covariant FeaturesFeature Detection; Feature ExtractionCodehttp://www.robots.ox.ac.uk/~vgg/research/affine/T. Tuytelaars and K. Mikolajczyk, Local Invariant Feature Detectors: A Survey, Foundations and Trends in Computer Graphics and Vision, 2008
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Groups of Adjacent Contour SegmentsFeature Detection; Feature ExtractionCodehttp://www.robots.ox.ac.uk/~vgg/share/ferrari/release-kas-v102.tgzV. Ferrari, L. Fevrier, F. Jurie, and C. Schmid, Groups of Adjacent Contour Segments for Object Detection, PAMI, 2007
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Superpixel by Gerg MoriImage SegmentationCodehttp://www.cs.sfu.ca/~mori/research/superpixels/X. Ren and J. Malik. Learning a classification model for segmentation. ICCV, 2003
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Efficient Graph-based Image Segmentation - C++ codeImage SegmentationCodehttp://people.cs.uchicago.edu/~pff/segment/P. Felzenszwalb and D. Huttenlocher. Efficient Graph-Based Image Segmentation, IJCV 2004
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Efficient Graph-based Image Segmentation - Matlab WrapperImage SegmentationCodehttp://www.mathworks.com/matlabcentral/fileexchange/25866-efficient-graph-based-image-segmentationP. Felzenszwalb and D. Huttenlocher. Efficient Graph-Based Image Segmentation, IJCV 2004
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Mean-Shift Image Segmentation - EDISONImage SegmentationCodehttp://coewww.rutgers.edu/riul/research/code/EDISON/index.htmlD. Comaniciu, P Meer. Mean Shift: A Robust Approach Toward Feature Space Analysis. PAMI 2002
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Mean-Shift Image Segmentation - Matlab WrapperImage SegmentationCodehttp://www.wisdom.weizmann.ac.il/~bagon/matlab_code/edison_matlab_interface.tar.gzD. Comaniciu, P Meer. Mean Shift: A Robust Approach Toward Feature Space Analysis. PAMI 2002
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OWT-UCM Hierarchical SegmentationImage SegmentationCodehttp://www.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/resources.htmlP. Arbelaez, M. Maire, C. Fowlkes and J. Malik. Contour Detection and Hierarchical Image Segmentation. PAMI, 2011
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TurbepixelsImage SegmentationCodehttp://www.cs.toronto.edu/~babalex/research.htmlA. Levinshtein, A. Stere, K. N. Kutulakos, D. J. Fleet, S. J. Dickinson, and K. Siddiqi, TurboPixels: Fast Superpixels Using Geometric Flows, PAMI 2009
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Quick-ShiftImage SegmentationCodehttp://www.vlfeat.org/overview/quickshift.htmlA. Vedaldi and S. Soatto, Quick Shift and Kernel Methodsfor Mode Seeking, ECCV, 2008
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SLIC SuperpixelsImage SegmentationCodehttp://ivrg.epfl.ch/supplementary_material/RK_SLICSuperpixels/index.htmlR. Achanta, A. Shaji, K. Smith, A. Lucchi, P. Fua, and S. Susstrunk, SLIC Superpixels, EPFL Technical Report, 2010
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Segmentation by Minimum Code LengthImage SegmentationCodehttp://perception.csl.uiuc.edu/coding/image_segmentation/A. Y. Yang, J. Wright, S. Shankar Sastry, Y. Ma , Unsupervised Segmentation of Natural Images via Lossy Data Compression, CVIU, 2007
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Biased Normalized CutImage SegmentationCodehttp://www.cs.berkeley.edu/~smaji/projects/biasedNcuts/S. Maji, N. Vishnoi and J. Malik, Biased Normalized Cut, CVPR 2011
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Multiscale Segmentation TreeImage SegmentationCodehttp://vision.ai.uiuc.edu/segmentationE. Akbas and N. Ahuja, “From ramp discontinuities to segmentation tree,” ACCV 2009;
N. Ahuja, “A Transform for Multiscale Image Segmentation by Integrated Edge and Region Detection,” PAMI 1996
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Entropy Rate Superpixel SegmentationImage SegmentationCodehttp://www.umiacs.umd.edu/~mingyliu/src/ers_matlab_wrapper_v0.1.zipM.-Y. Liu, O. Tuzel, S. Ramalingam, and R. Chellappa, Entropy Rate Superpixel Segmentation, CVPR 2011
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Viola-Jones Object DetectionObject DetectionCodehttp://pr.willowgarage.com/wiki/FaceDetectionP. Viola and M. Jones, Rapid Object Detection Using a Boosted Cascade of Simple Features, CVPR, 2001
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A simple object detector with boostingObject DetectionCodehttp://people.csail.mit.edu/torralba/shortCourseRLOC/boosting/boosting.htmlICCV 2005 short courses on Recognizing and Learning Object Categories
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Cascade Object Detection with Deformable Part ModelsObject DetectionCodehttp://people.cs.uchicago.edu/~rbg/star-cascade/P. Felzenszwalb, R. Girshick, D. McAllester. Cascade Object Detection with Deformable Part Models. CVPR, 2010
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PoseletObject DetectionCodehttp://www.eecs.berkeley.edu/~lbourdev/poselets/L. Bourdev, J. Malik, Poselets: Body Part Detectors Trained Using 3D Human Pose Annotations, ICCV 2009
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Implicit Shape ModelObject DetectionCodehttp://www.vision.ee.ethz.ch/~bleibe/code/ism.htmlB. Leibe, A. Leonardis, B. Schiele. Robust Object Detection with Interleaved Categorization and Segmentation, IJCV, 2008
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A simple parts and structure object detectorObject DetectionCodehttp://people.csail.mit.edu/fergus/iccv2005/partsstructure.htmlICCV 2005 short courses on Recognizing and Learning Object Categories
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Max-Margin Hough TransformObject DetectionCodehttp://www.cs.berkeley.edu/~smaji/projects/max-margin-hough/S. Maji and J. Malik, Object Detection Using a Max-Margin Hough Transform. CVPR 2009
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Ensemble of Exemplar-SVMsObject DetectionCodehttp://www.cs.cmu.edu/~tmalisie/projects/iccv11/T. Malisiewicz, A. Gupta, A. Efros. Ensemble of Exemplar-SVMs for Object Detection and Beyond . ICCV, 2011
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Recognition using regionsObject DetectionCodehttp://www.cs.berkeley.edu/~chunhui/publications/cvpr09_v2.zipC. Gu, J. J. Lim, P. Arbelaez, and J. Malik, CVPR 2009
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Closed Form MattingAlpha MattingCodehttp://people.csail.mit.edu/alevin/matting.tar.gzA. Levin D. Lischinski and Y. Weiss. A Closed Form Solution to Natural Image Matting, PAMI 2008.
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Spectral MattingAlpha MattingCodehttp://www.vision.huji.ac.il/SpectralMatting/A. Levin, A. Rav-Acha, D. Lischinski. Spectral Matting. PAMI 2008
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Learning-based MattingAlpha MattingCodehttp://www.mathworks.com/matlabcentral/fileexchange/31412Y. Zheng and C. Kambhamettu, Learning Based Digital Matting, ICCV 2009
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Bayesian MattingAlpha MattingCodehttp://www1.idc.ac.il/toky/CompPhoto-09/Projects/Stud_projects/Miki/index.htmlY. Y. Chuang, B. Curless, D. H. Salesin, and R. Szeliski, A Bayesian Approach to Digital Matting, CVPR, 2001
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Shared MattingAlpha MattingCodehttp://www.inf.ufrgs.br/~eslgastal/SharedMatting/E. S. L. Gastal and M. M. Oliveira, Computer Graphics Forum, 2010
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Fast Bilateral FilterImage FilteringCodehttp://people.csail.mit.edu/sparis/bf/S. Paris and F. Durand, A Fast Approximation of the Bilateral Filter using a Signal Processing Approach, ECCV, 2006
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Weighted Least Squares FilterImage FilteringCodehttp://www.cs.huji.ac.il/~danix/epd/Z. Farbman, R. Fattal, D. Lischinski, R. Szeliski, Edge-Preserving Decompositions for Multi-Scale Tone and Detail Manipulation, SIGGRAPH 2008
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Domain TransformationImage FilteringCodehttp://inf.ufrgs.br/~eslgastal/DomainTransform/DomainTransformFilters-Source-v1.0.zipE. Gastal, M. Oliveira, Domain Transform for Edge-Aware Image and Video Processing, SIGGRAPH 2011
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Local Laplacian FiltersImage FilteringCodehttp://people.csail.mit.edu/sparis/publi/2011/siggraph/matlab_source_code.zipS. Paris, S. Hasinoff, J. Kautz, Local Laplacian Filters: Edge-Aware Image Processing with a Laplacian Pyramid, SIGGRAPH 2011
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Image smoothing via L0 Gradient MinimizationImage FilteringCodehttp://www.cse.cuhk.edu.hk/~leojia/projects/L0smoothing/L0smoothing.zipL. Xu, C. Lu, Y. Xu, J. Jia, Image smoothing via L0 Gradient Minimization, SIGGRAPH Asia 2011
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Guided Image FilteringImage FilteringCodehttp://personal.ie.cuhk.edu.hk/~hkm007/eccv10/guided-filter-code-v1.rarK. He, J. Sun, X. Tang, Guided Image Filtering, ECCV 2010
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Anisotropic DiffusionImage FilteringCodehttp://www.mathworks.com/matlabcentral/fileexchange/14995-anisotropic-diffusion-perona-malikP. Perona and J. Malik, Scale-space and edge detection using anisotropic diffusion, PAMI 1990
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Real-time O(1) Bilateral FilteringImage FilteringCodehttp://vision.ai.uiuc.edu/~qyang6/publications/code/qx_constant_time_bilateral_filter_ss.zipQ. Yang, K.-H. Tan and N. Ahuja, Real-time O(1) Bilateral Filtering,
CVPR 2009
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SVM for Edge-Preserving FilteringImage FilteringCodehttp://vision.ai.uiuc.edu/~qyang6/publications/code/cvpr-10-svmbf/program_video_conferencing.zipQ. Yang, S. Wang, and N. Ahuja, SVM for Edge-Preserving Filtering,
CVPR 2010
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Edge Foci Interest PointsFeature DetectionCodehttp://research.microsoft.com/en-us/um/people/larryz/edgefoci/edge_foci.htmL. Zitnickand K. Ramnath, Edge Foci Interest Points, ICCV, 2011
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K-SVDImage DenoisingCodehttp://www.cs.technion.ac.il/~ronrubin/Software/ksvdbox13.zip
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BLS-GSMImage DenoisingCodehttp://decsai.ugr.es/~javier/denoise/
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BM3DImage DenoisingCodehttp://www.cs.tut.fi/~foi/GCF-BM3D/
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Field of ExpertsImage DenoisingCodehttp://www.cs.brown.edu/~roth/research/software.html
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Gaussian Field of ExpertsImage DenoisingCodehttp://www.cs.huji.ac.il/~yweiss/BRFOE.zip
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Non-local MeansImage DenoisingCodehttp://dmi.uib.es/~abuades/codis/NLmeansfilter.m
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Kernel RegressionsImage DenoisingCodehttp://www.soe.ucsc.edu/~htakeda/MatlabApp/KernelRegressionBasedImageProcessingToolBox_ver1-1beta.zip
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Efficient Belief Propagation for Early VisionImage Denoising; Stereo MatchingCodehttp://www.cs.brown.edu/~pff/bp/P. F. Felzenszwalb and D. P. Huttenlocher, Efficient Belief Propagation for Early Vision, IJCV, 2006
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Clustering-based DenoisingImage DenoisingCodehttp://users.soe.ucsc.edu/~priyam/K-LLD/P. Chatterjee and P. Milanfar, Clustering-based Denoising with Locally Learned Dictionaries (K-LLD), TIP, 2009
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Sparsity-based Image DenoisingImage DenoisingCodehttp://www.csee.wvu.edu/~xinl/CSR.htmlW. Dong, X. Li, L. Zhang and G. Shi, Sparsity-based Image Denoising vis Dictionary Learning and Structural Clustering, CVPR, 2011
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Learning Models of Natural Image PatchesImage Denoising; Image Super-resolution; Image DeblurringCodehttp://www.cs.huji.ac.il/~daniez/D. Zoran and Y. Weiss, From Learning Models of Natural Image Patches to Whole Image Restoration, ICCV, 2011
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Hough Forests for Object DetectionObject DetectionCodehttp://www.vision.ee.ethz.ch/~gallju/projects/houghforest/index.htmlJ. Gall and V. Lempitsky, Class-Specific Hough Forests for Object Detection, CVPR, 2009
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Lucas-Kanade affine template trackingVisual TrackingCodehttp://www.mathworks.com/matlabcentral/fileexchange/24677-lucas-kanade-affine-template-trackingS. Baker and I. Matthews, Lucas-Kanade 20 Years On: A Unifying Framework, IJCV 2002
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EasyCamCalibCamera CalibrationCodehttp://arthronav.isr.uc.pt/easycamcalib/J. Barreto, J. Roquette, P. Sturm, and F. Fonseca, Automatic camera calibration applied to medical endoscopy, BMVC, 2009
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3D Gradients (HOG3D)Action RecognitionCodehttp://lear.inrialpes.fr/people/klaeser/research_hog3dA. Klaser, M. Marszałek, and C. Schmid, BMVC, 2008.
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Dense Trajectories Video DescriptionAction RecognitionCodehttp://lear.inrialpes.fr/people/wang/dense_trajectoriesH. Wang and A. Klaser and C. Schmid and C.- L. Liu, Action Recognition by Dense Trajectories, CVPR, 2011
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ClassCut for Unsupervised Class SegmentationObject SegmentationCodehttp://www.vision.ee.ethz.ch/~calvin/classcut/ClassCut-release.zipB. Alexe, T. Deselaers and V. Ferrari, ClassCut for Unsupervised Class Segmentation, ECCV 2010
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Global and Efficient Self-SimilarityFeature ExtractionCodehttp://www.vision.ee.ethz.ch/~calvin/gss/selfsim_release1.0.tgzT. Deselaers, V. Ferrari, Global and Efficient Self-Similarity for Object Classification and Detection, CVPR 2010
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Calvin Upper-Body DetectorPose EstimationCodehttp://www.vision.ee.ethz.ch/~calvin/calvin_upperbody_detector/E. Marcin, F. Vittorio, Better Appearance Models for Pictorial Structures, BMVC 2009
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Horn and Schunck's Optical FlowOptical FlowCodehttp://www.cs.brown.edu/~dqsun/code/hs.zip
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Black and Anandan's Optical FlowOptical FlowCodehttp://www.cs.brown.edu/~dqsun/code/ba.zip
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Optical Flow by Deqing SunOptical FlowCodehttp://www.cs.brown.edu/~dqsun/code/flow_code.zipD. Sun, S. Roth, M. J. Black, Secrets of Optical Flow Estimation and Their Principles, CVPR, 2010
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L1 TrackingVisual TrackingCodehttp://www.dabi.temple.edu/~hbling/code_data.htmX. Mei and H. Ling, Robust Visual Tracking using L1 Minimization, ICCV, 2009
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Efficient Earth Mover's Distance with L1 Ground Distance (EMD_L1)Kernels and DistancesCodehttp://www.dabi.temple.edu/~hbling/code/EmdL1_v3.zipH. Ling and K. Okada, An Efficient Earth Mover's Distance Algorithm for Robust Histogram Comparison, PAMI 2007
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Diffusion-based distanceKernels and DistancesCodehttp://www.dabi.temple.edu/~hbling/code/DD_v1.zipH. Ling and K. Okada, Diffusion Distance for Histogram Comparison, CVPR 2006
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Particle Filter Object TrackingVisual TrackingCodehttp://blogs.oregonstate.edu/hess/code/particles/
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GPU Implementation of Kanade-Lucas-Tomasi Feature TrackerVisual TrackingCodehttp://cs.unc.edu/~ssinha/Research/GPU_KLT/S. N Sinha, J.-M. Frahm, M. Pollefeys and Y. Genc, Feature Tracking and Matching in Video Using Programmable Graphics Hardware, MVA, 2007
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Space-Time Interest Points (STIP) Feature Extraction; Action RecognitionCodehttp://www.nada.kth.se/cvap/abstracts/cvap284.htmlI. Laptev and T. Lindeberg, On Space-Time Interest Points, IJCV 2005
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KLT: An Implementation of the Kanade-Lucas-Tomasi Feature TrackerVisual TrackingCodehttp://www.ces.clemson.edu/~stb/klt/B. D. Lucas and T. Kanade. An Iterative Image Registration Technique with an Application to Stereo Vision. IJCAI, 1981
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Camera Calibration Toolbox for MatlabCamera CalibrationCodehttp://www.vision.caltech.edu/bouguetj/calib_doc/http://www.vision.caltech.edu/bouguetj/calib_doc/htmls/ref.html
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The Pyramid Match: Efficient Matching for Retrieval and RecognitionFeature Matching; Image ClassificationCodehttp://www.cs.utexas.edu/~grauman/research/projects/pmk/pmk_projectpage.htmK. Grauman and T. Darrell. The Pyramid Match Kernel: Discriminative Classification with Sets of Image Features, ICCV 2005
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Piotr's Image & Video Matlab ToolboxImage Processing; Image FilteringCodehttp://vision.ucsd.edu/~pdollar/toolbox/doc/index.htmlPiotr Dollar, Piotr's Image & Video Matlab Toolbox, http://vision.ucsd.edu/~pdollar/toolbox/doc/index.html
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Epipolar Geometry ToolboxCamera CalibrationCodehttp://egt.dii.unisi.it/G.L. Mariottini, D. Prattichizzo, EGT: a Toolbox for Multiple View Geometry and Visual Servoing, IEEE Robotics & Automation Magazine, 2005
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Matlab Functions for Multiple View GeometryMultiple View GeometryCodehttp://www.robots.ox.ac.uk/~vgg/hzbook/code/
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MATLAB and Octave Functions
for Computer Vision and Image Processing		Multiple View GeometryCodehttp://www.csse.uwa.edu.au/~pk/Research/MatlabFns/index.htmlP. D. Kovesi. MATLAB and Octave Functions for Computer Vision and Image Processing, http://www.csse.uwa.edu.au/~pk/research/matlabfns
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Motion Tracking in Image SequencesVisual TrackingCodehttp://www.cs.berkeley.edu/~flw/tracker/ C. Stauffer and W. E. L. Grimson. Learning patterns of activity using real-time tracking, PAMI, 2000