This letter presents a novel approach for logo retrieval. Considering the fact that logo only occupies a small portion of an image, we apply Faster R-CNN to detect logo proposals first, and then use a two-step pooling strategy with adaptive weight to obtain an accurate global signature. The adaptive weighted pooling method can effectively balance the recall and precision of proposals by incorporating the probability of each proposal being a logo. Experimental results show that the proposed method interprets the similarity between query and database image more accurately and achieves state of the art performance.

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recall precision adaptive weighted pooling method global signature twostep pooling strategy logo proposals database faster rcnn approach similarity performance

Cunzhao Shi, Chunheng Wang, Baihua Xiao,Chengzuo Qi,.Logo Retrieval Using Logo Proposals and Adaptive Weighted Pooling. 24 (4),442-445.

Cunzhao Shi, et al."Logo Retrieval Using Logo Proposals and Adaptive Weighted Pooling" 24

Cunzhao Shi, Chunheng Wang, Baihua Xiao,Chengzuo Qi,"Logo Retrieval Using Logo Proposals and Adaptive Weighted Pooling"