Transformed Anti-Sparse Hashing

Zhangyang Wang, Ji Liu, Shuai Huang, Xinchao Wang and Shiyu Chang

Abstract

Anti-sparse representation was recently considered for unsupervised hashing, due to its remarkable robustness to the binary quantization error. We relax the existing spread property [4, 22] for anti-sparse solutions, to a new Relaxed Spread Property (RSP) that demands milder conditions. We then propose a novel Transformed Anti-Sparse Hashing (TASH) model to overcome several major bottlenecks, that have significantly limited the effectiveness of anti-sparse hashing models. TASH jointly learns a dimension-reduction transform, a dictionary and the anti-sparse representations in a unified formulation.

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DOI

10.5244/C.31.37
https://dx.doi.org/10.5244/C.31.37

Citation

Zhangyang Wang, Ji Liu, Shuai Huang, Xinchao Wang and Shiyu Chang. Transformed Anti-Sparse Hashing. In T.K. Kim, S. Zafeiriou, G. Brostow and K. Mikolajczyk, editors, Proceedings of the British Machine Vision Conference (BMVC), pages 37.1-37.12. BMVA Press, September 2017.

Bibtex

            @inproceedings{BMVC2017_37,
                title={Transformed Anti-Sparse Hashing},
                author={Zhangyang Wang, Ji Liu, Shuai Huang, Xinchao Wang and Shiyu Chang},
                year={2017},
                month={September},
                pages={37.1-37.12},
                articleno={37},
                numpages={12},
                booktitle={Proceedings of the British Machine Vision Conference (BMVC)},
                publisher={BMVA Press},
                editor={Tae-Kyun Kim, Stefanos Zafeiriou, Gabriel Brostow and Krystian Mikolajczyk},
                doi={10.5244/C.31.37},
                isbn={1-901725-60-X},
                url={https://dx.doi.org/10.5244/C.31.37}
            }