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 |
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Optical Flow |
Black and Anandan's Optical Flow |
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Pose Estimation |
Training Deformable Models for Localization |
Ramanan, D. "Learning to Parse Images of Articulated Bodies."NIPS 2006 |
|
Pose Estimation |
Calvin Upper-Body Detector |
E. Marcin, F. Vittorio, Better Appearance Models for Pictorial Structures, BMVC 2009 |
|
Pose Estimation |
Articulated Pose Estimation using Flexible Mixtures of Parts |
Y. Yang, D. Ramanan, Articulated Pose Estimation using Flexible Mixtures of Parts, CVPR 2011 |
|
Pose Estimation |
Estimating Human Pose from Occluded Images |
J.-B. Huang and M.-H. Yang, Estimating Human Pose from Occluded Images, ACCV 2009 |
|
Saliency Detection |
Saliency detection: A spectral residual approach |
X. Hou and L. Zhang. Saliency detection: A spectral residual approach. CVPR, 2007 |
|
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 |
|
Saliency Detection |
Attention via Information Maximization |
N. Bruce and J. Tsotsos. Saliency based on information maximization. In NIPS, 2005 |
|
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 |
|
Saliency Detection |
Frequency-tuned salient region detection |
R. Achanta, S. Hemami, F. Estrada, and S. Susstrunk.Frequency-tuned salient region detection. In CVPR, 2009 |
|
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 |
|
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 |
|
Saliency Detection |
Graph-based visual saliency |
J. Harel, C. Koch, and P. Perona. Graph-based visual saliency.NIPS, 2007 |
|
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 |
|
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 |
|
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 |
|
Saliency Detection |
Context-aware saliency detection |
S. Goferman, L. Zelnik-Manor, and A. Tal. Context-aware saliency detection. In CVPR, 2010. |
|
Saliency Detection |
Saliency detection using maximum symmetric surround |
R. Achanta and S. Susstrunk. Saliency detection using maximum symmetric surround. In ICIP, 2010 |
|
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 |
|
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 |
|
Sparse Representation |
Efficient sparse coding algorithms |
H. Lee, A. Battle, R. Rajat and AY Ng, Efficient sparse coding algorithms, NIPS 2007 |
|
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 |
|
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 |
|
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 |
|
Sparse Representation |
SPArse Modeling Software |
J. Mairal, F. Bach, J. Ponce and G. Sapiro. Online Learning for Matrix Factorization and Sparse Coding, JMLR 2010 |
|
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 |
|
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 |
|
Stereo |
Constant-Space Belief Propagation |
Q. Yang, L. Wang, and N. Ahuja, A Constant-Space Belief Propagation Algorithm for Stereo Matching, CVPR 2010 |
|
Stereo |
Stereo Evaluation |
D. Scharstein and R. Szeliski. A taxonomy and evaluation of dense two-frame stereo correspondence algorithms, IJCV 2001 |
|
Image Denoising andStereo Matching |
Efficient Belief Propagation for Early Vision |
PF Felzenszwalb and DP Huttenlocher, Efficient Belief Propagation for Early Vision, IJCV, 2006 |
|
Structure from motion |
Nonrigid Structure From Motion in Trajectory Space |
||
Structure from motion |
libmv |
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Structure from motion |
Bundler |
N. Snavely, S M. Seitz, R Szeliski. Photo Tourism: Exploring image collections in 3D. SIGGRAPH 2006 |
|
Structure from motion |
FIT3D |
||
Structure from motion |
VisualSFM : A Visual Structure from Motion System |
||
Structure from motion |
OpenSourcePhotogrammetry |
||
Structure from motion |
Structure and Motion Toolkit in Matlab |
||
Structure from motion |
Structure from Motion toolbox for Matlab by Vincent Rabaud |
||
Subspace Learning |
Generalized Principal Component Analysis |
R. Vidal, Y. Ma and S. Sastry. Generalized Principal Component Analysis (GPCA), CVPR 2003 |
|
Text Recognition |
Text recognition in the wild |
K. Wang, B. Babenko, and S. Belongie, End-to-end Scene Text Recognition, ICCV 2011 |
|
Text Recognition |
Neocognitron for handwritten digit recognition |
K. Fukushima: "Neocognitron for handwritten digit recognition", Neurocomputing, 2003 |
|
Texture Synthesis |
Image Quilting for Texture Synthesis and Transfer |
AA Efros and WT Freeman, Image Quilting for Texture Synthesis and Transfer, SIGGRAPH 2001 |
Topic |
Name |
Reference |
code |
|
Visual Tracking |
GPU Implementation of Kanade-Lucas-Tomasi Feature |
S. N Sinha, J.-M. Frahm, M. |
||
Visual Tracking |
Superpixel Tracking |
S. Wang, H. Lu, F. Yang, and |
||
Visual Tracking |
Tracking with Online Multiple Instance |
B. Babenko, M.-H. Yang, S. |
||
Visual Tracking |
Motion Tracking in Image Sequences |
C. Stauffer and WEL |
||
Visual Tracking |
L1 Tracking |
X. Mei and H. Ling, Robust Visual Tracking using |
||
Visual Tracking |
Online Discriminative Object Tracking with Local |
Q. Wang, F. Chen, W. Xu, and |
||
Visual Tracking |
KLT: An Implementation of the Kanade-Lucas-Tomasi |
BD Lucas and T. Kanade. An |
||
Visual Tracking |
Online boosting trackers |
H. Grabner, and H. Bischof, On-line Boosting and |
||
Visual Tracking |
Visual Tracking Decomposition |
J Kwon and KM Lee, Visual Tracking Decomposition, |
||
Visual Tracking |
Globally-Optimal Greedy Algorithms for Tracking a |
H. Pirsiavash, D. Ramanan, C. |
||
Visual Tracking |
Lucas-Kanade affine template tracking |
S. Baker and I. Matthews, Lucas-Kanade 20 Years |
||
Visual Tracking |
Object Tracking |
A. Yilmaz, O. Javed and M. Shah, Object Tracking: |
||
Visual Tracking |
Visual Tracking with Histograms and Articulating |
SM Shshed Nejhum, J. Ho, and M.-H.Yang, Visual |
||
Visual Tracking |
Tracking using Pixel-Wise Posteriors |
C. Bibby and I. Reid, Tracking using Pixel-Wise |
||
Visual Tracking |
Incremental Learning for Robust Visual |
D. Ross, J. Lim, R.-S. Lin, |
||
Visual Tracking |
Particle Filter Object Tracking |
一共248篇。one:47、two:45、three:
49、four:
47、five:
44、six:
16。
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