Iterative local re-ranking with attribute guided synthesis for face sketch recognition
Iterative local re-ranking with attribute guided synthesis for face sketch recognition
复制标题
用于面部草图识别的属性引导合成的迭代局部重排序
DOI：
10.1016/j.patcog.2020.107579
复制
发表时间：
2021-01-01
影响因子：
8
通讯作者：
Li, Jie
中科院分区：
文献类型：
--
作者：
Liu, Decheng;Gao, Xinbo;Li, Jie
Because of the large texture and spatial structure discrepancies between face sketches and photos, face sketch recognition becomes a challenging problem in face recognition community. For example, in law enforcement and security, the specific face sketch generation process could introduce some inevitable biases which results in poor face sketch recognition performance. In order to mimic the modality gap introduced by the biases during face sketch creation process, the novel iterative local re-ranking with attribute guided synthesis method is proposed for face sketch recognition, which does not require any extra manually annotation or human interaction. The clues of face attributes are utilized to generate images with varying local characteristic from probe sketches, which could help eliminate the unavoidable biases. Considering the special property of face sketches, the iterative local re-ranking algorithm is designed to encode the contextual information integrated with local invariant discriminative information for matching sketches with photos. Experimental results on multiple face sketch databases demonstrate that the proposed method achieves superior performances compared with state-of-the-art methods. (C) 2020 Elsevier Ltd. All rights reserved.
