2020
Local-Global Feature for Video-Based One-Shot Person Re-Identification
ICASSP 2020accepted
One-shot video-based re-identification, which uses only one labeled tracklet for each identity, is challenging since the framework usually suffers misalignment and inefficient utilizing of unlabeled data. In this paper we propose a novel local-global progressive learning framework to overcome the li…