Uncertainty-Aware Multi-Shot Knowledge Distillation for Image-Based Object Re-Identification

Understand

Object re-identification (re-id) aims to identify a specific object across times or camera views, with the person re-id and vehicle re-id as the most widely studied applications.

• Re-id is challenging because of the variations in viewpoints, (human) poses, and occlusions.
• Multi-shots of the same object can cover diverse viewpoints/poses and thus provide more comprehensive information.
• In this paper, we propose exploiting the multi-shots of the same identity to guide the feature learning of each individual image.