CVPR2013-papers

1,PISA: Pixelwise Image Saliency by Aggregating Complementary Appearance Contrast Measures with Spatial Priors
Keyang Shi, Keze Wang, Jiangbo Lu, Liang Lin

http://ss.sysu.edu.cn/~ll/publications.html

2,Looking Beyond the Image: Unsupervised Learning for Object Saliency and Detection
Parthipan Siva, Chris Russell, Tao Xiang, Lourdes Agapito

http://www.eecs.qmul.ac.uk/~lourdes/

3, Hierarchical Saliency Detection
Qiong Yan, Li Xu, Jianping Shi, Jiaya Jia

4,Saliency Detection via Graph-Based Manifold Ranking
Chuan Yang, Lihe Zhang, Huchuan Lu, Ming-Hsuan Yang, Xiang Ruan

http://faculty.ucmerced.edu/mhyang/pubs.html

5, Saliency Aggregation: A Data-driven Approach
Long Mai, Yuzhen Niu, Feng Liu

http://web.cecs.pdx.edu/~fliu/publication.htm

6,What Makes a Patch Distinct?[PDF]
Ran Margolin, Ayellet Tal, Lihi Zelnik-Manor

[code] http://cgm.technion.ac.il/Computer-Graphics-Multimedia/Software/DstnctSal/

Low-level processing:

Finding Things: Image Parsing with Regions and Per-Exemplar Detectors
Joseph Tighe, Svetlana Lazebnik

 

Bringing Semantics Into Focus Using Visual Abstraction
Larry Zitnick, Devi Parikh

 

PatchMatch Filter: Efficient Edge-Aware Filtering Meets Randomized Search for Fast Correspondence Field Estimation
Jiangbo Lu, Hongsheng Yang, Dongbo Min, Minh Do

 

Boosting Binary Keypoint Descriptors
Tomasz Trzcinski, Mario Christoudias, Pascal Fua, Vincent Lepetit