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Poster
Compact Generalized Non-local Network
Kaiyu Yue · Ming Sun · Yuchen Yuan · Feng Zhou · Errui Ding · Fuxin Xu

Tue Dec 04 02:00 PM -- 04:00 PM (PST) @ Room 210 #38
in Tue Poster Session B »

The non-local module is designed for capturing long-range spatio-temporal dependencies in images and videos. Although having shown excellent performance, it lacks the mechanism to model the interactions between positions across channels, which are of vital importance in recognizing fine-grained objects and actions. To address this limitation, we generalize the non-local module and take the correlations between the positions of any two channels into account. This extension utilizes the compact representation for multiple kernel functions with Taylor expansion that makes the generalized non-local module in a fast and low-complexity computation flow. Moreover, we implement our generalized non-local method within channel groups to ease the optimization. Experimental results illustrate the clear-cut improvements and practical applicability of the generalized non-local module on both fine-grained object recognition and video classification. Code is available at: https://github.com/KaiyuYue/cgnl-network.pytorch.

Keywords: Computer Vision · Classification
[ Paper]  [ Poster] 

Author Information

Kaiyu Yue (Baidu Inc.)
Ming Sun (baidu)
Yuchen Yuan (Baidu Inc.)
Feng Zhou (Carnegie Mellon University)
Errui Ding (Baidu Inc.)
Fuxin Xu (Central South University)

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