关键词: 跨域行人重识别, 域自适应, 不变性

Abstract:

When tested in another domain, the person Re-identification（ReID） model trained in a single domain has a huge performance drop, in order to solve this problem, an algorithm combining the changes of inter-domain and intra-domain is proposed. Firstly, the PR strategy is used to partition the person feature map to improve the model generalization ability. Then, for the change of the inter-domain, pose-invariance between the domains is introduced to narrow the posture gap between person in the source and target domains. Finally, for intra-domain changes, pose-invariance in a domain, sample-invariance, neighborhood-invariance and camera-invariance are introduced to increase the distance between different person and reduce the distance between the same person. Experiments demonstrate that the PR strategy and five invariance properties effectively enhance the domain adaptability in cross-domain person ReID. At the same time, the recognition accuracy is effectively improved compared with algorithms that focus only on inter-domain changes or intra-domain changes.

Key words: cross-domain person re-identification, domain adaptation, invariance