Topic
Resources
References
Category-Independent Object Proposal
· Objectness measure [1] [Code]
· Parametric min-cut [2] [Project]
· Object proposal [3] [Project]
1. B. Alexe, T. Deselaers, V. Ferrari, What is an Object?, CVPR 2010 [PDF]
2. J. Carreira and C. Sminchisescu. Constrained Parametric Min-Cuts for Automatic Object Segmentation, CVPR 2010. [PDF]
3. I. Endres and D. Hoiem. Category Independent Object Proposals, ECCV 2010. [PDF]
MRF
· Graph Cut [Project] [C++/Matlab Wrapper Code]
1. Y. Boykov, O. Veksler and R. Zabih, Fast Approximate Energy Minimization via Graph Cuts, PAMI 2001 [PDF]
Shadow Detection
· Shadow Detection using Paired Region [Project]
· Ground shadow detection [Project]
1. R. Guo, Q. Dai and D. Hoiem, Single-Image Shadow Detection and Removal using Paired Regions, CVPR 2011 [PDF]
2. J.-F. Lalonde, A. A. Efros, S. G. Narasimhan, Detecting Ground Shadowsin Outdoor Consumer Photographs, ECCV 2010 [PDF]
Optical Flow
· Kanade-Lucas-Tomasi Feature Tracker [C Code]
· Optical Flow Matlab/C++ code by Ce Liu [Project]
· Horn and Schunck's method by Deqing Sun [Code]
· Black and Anandan's method by Deqing Sun [Code]
· Optical flow code by Deqing Sun [Matlab Code] [Project]
· Large Displacement Optical Flow by Thomas Brox [Executable for 64-bit Linux] [ Matlab Mex-functions for 64-bit Linux and 32-bit Windows] [Project]
· Variational Optical Flow by Thomas Brox [Executable for 64-bit Linux] [ Executable for 32-bit Windows ] [ Matlab Mex-functions for 64-bit Linux and 32-bit Windows ] [Project]
1. B.D. Lucas and T. Kanade, An Iterative Image Registration Technique with an Application to Stereo Vision, IJCAI 1981. [PDF]
2. J. Shi, C. Tomasi, Good Feature to Track, CVPR 1994. [PDF]
3. C. Liu. Beyond Pixels: Exploring New Representations and Applications for Motion Analysis. Doctoral Thesis. MIT 2009. [PDF]
4. B.K.P. Horn and B.G. Schunck, Determining Optical Flow, Artificial Intelligence 1981. [PDF]
5. M. J. Black and P. Anandan, A framework for the robust estimation of optical flow, ICCV 93. [PDF]
6. D. Sun, S. Roth, and M. J. Black, Secrets of optical flow estimation and their principles, CVPR 2010. [PDF]
7. T. Brox, J. Malik, Large displacement optical flow: descriptor matching in variational motion estimation, PAMI, 2010 [PDF]
8. T. Brox, A. Bruhn, N. Papenberg, J. Weickert, High accuracy optical flow estimation based on a theory for warping, ECCV 2004 [PDF]
Object Tracking
· Particle filter object tracking [1] [Project]
· KLT Tracker [2-3] [Project]
· MILTrack [4] [Code]
· Incremental Learning for Robust Visual Tracking [5] [Project]
· Online Boosting Trackers [6-7] [Project]
· L1 Tracking [8] [Matlab code]
1. P. Perez, C. Hue, J. Vermaak, and M. Gangnet. Color-Based Probabilistic Tracking ECCV, 2002. [PDF]
2. B.D. Lucas and T. Kanade, An Iterative Image Registration Technique with an Application to Stereo Vision, IJCAI 1981. [PDF]
3. J. Shi, C. Tomasi, Good Feature to Track, CVPR 1994. [PDF]
4. B. Babenko, M. H. Yang, S. Belongie, Robust Object Tracking with Online Multiple Instance Learning, PAMI 2011 [PDF]
5. D. Ross, J. Lim, R.-S. Lin, M.-H. Yang, Incremental Learning for Robust Visual Tracking, IJCV 2007 [PDF]
6. H. Grabner, and H. Bischof, On-line Boosting and Vision, CVPR 2006 [PDF]
7. H. Grabner, C. Leistner, and H. Bischof, Semi-supervised On-line Boosting for Robust Tracking, ECCV 2008 [PDF]
8. X. Mei and H. Ling, Robust Visual Tracking using L1 Minimization, ICCV, 2009. [PDF]
Image Matting
· Closed Form Matting [Code]
· Spectral Matting [Project]
· Learning-based Matting [Code]
1. A. Levin D. Lischinski and Y. Weiss. A Closed Form Solution to Natural Image Matting, PAMI 2008 [PDF]
2. A. Levin, A. Rav-Acha, D. Lischinski. Spectral Matting. PAMI 2008. [PDF]
3. Y. Zheng and C. Kambhamettu, Learning Based Digital Matting, ICCV 2009 [PDF]
Bilateral Filtering
· Fast Bilateral Filter [Project]
· Real-time O(1) Bilateral Filtering [Code]
· SVM for Edge-Preserving Filtering [Code]
1. Q. Yang, K.-H. Tan and N. Ahuja, Real-time O(1) Bilateral Filtering,
CVPR 2009. [PDF]
2. Q. Yang, S. Wang, and N. Ahuja, SVM for Edge-Preserving Filtering,
CVPR 2010. [PDF]
Image Denoising
· K-SVD [Matlab code]
· BLS-GSM [Project]
· BM3D [Project]
· FoE [Code]
· GFoE [Code]
· Non-local means [Code]
· Kernel regression [Code]
Image Super-Resolution
· MRF for image super-resolution [Project]
· Multi-frame image super-resolution [Project]
· UCSC Super-resolution [Project]
· Sprarse coding super-resolution [Code]
Image Deblurring
· Eficient Marginal Likelihood Optimization in Blind Deconvolution [Code]
· Analyzing spatially varying blur [Project]
· Radon Transform [Code]
Image Quality Assessment
· FSIM [1] [Project]
· Degradation Model [2] [Project]
· SSIM [3] [Project]
· SPIQA [Code]
1. L. Zhang, L. Zhang, X. Mou and D. Zhang, FSIM: A Feature Similarity Index for Image Quality Assessment, TIP 2011. [PDF]
2. N. Damera-Venkata, and T. D. Kite, W. S. Geisler, B. L. Evans, and A. C. Bovik,Image Quality Assessment Based on a Degradation Model, TIP 2000. [PDF]
3. Z. Wang, A. C. Bovik, H. R. Sheikh and E. P. Simoncelli, Image quality assessment: from error visibility to structural similarity, TIP 2004. [PDF]
4. B. Ghanem, E. Resendiz, and N. Ahuja, Segmentation-Based Perceptual Image Quality Assessment (SPIQA), ICIP 2008. [PDF]
Density Estimation
· Kernel Density Estimation Toolbox [Project]
Dimension Reduction
· Dimensionality Reduction Toolbox [Project]
· ISOMAP [Code]
· LLE [Project]
· Laplacian Eigenmaps [Code]
· Diffusion maps [Code]
Sparse Coding
Low-Rank Matrix Completion
Nearest Neighbors matching
· ANN: Approximate Nearest Neighbor Searching [Project] [Matlab wrapper]
· FLANN: Fast Library for Approximate Nearest Neighbors [Project]
Steoreo
· StereoMatcher [Project]
1. D. Scharstein and R. Szeliski. A taxonomy and evaluation of dense two-frame stereo correspondence algorithms, IJCV 2002 [PDF]
Structure from motion
· Boundler [1] [Project]
1. N. Snavely, S. M. Seitz, R. Szeliski. Photo Tourism: Exploring image collections in 3D. SIGGRAPH, 2006. [PDF]
Distance Transformation
· Distance Transforms of Sampled Functions [1] [Project]
1. P. F. Felzenszwalb and D. P. Huttenlocher. Distance transforms of sampled functions. Technical report, Cornell University, 2004. [PDF]
Chamfer Matching
· Fast Directional Chamfer Matching [Code]
1. M.-Y. Liu, O. Tuzel, A. Veeraraghavan, and R. Chellappa, Fast Directional Chamfer Matching, CVPR 2010 [PDF]
Clustering
· K-Means [VLFeat] [Oxford code]
· Spectral Clustering [UW Project][Code] [Self-Tuning code]
· Affinity Propagation [Project]
Classification
· SVM [Libsvm] [SVM-Light] [SVM-Struct]
· Boosting
· Naive Bayes
Regression
· SVM
· RVM
· GPR