Occluded Cloth-Changing Person Re-Identification via Occlusion-aware Appearance and Shape Reasoning

Existing methods in Person Re-Identification (ReID) often fail when simultaneously confronted with occlusions and clothing changes. In this paper, we introduce a challenging yet practical task called Occluded Cloth-Changing Re-ID (OCCRe-ID/). We propose Occlusion-aware Appearance and Shape Reasoning, the first framework OCCReID. We first propose an occlusion synthesis strategy to expose the model to real-world occlusion variations. We mitigate clothing changes by coupling silhouette-based body shape information with appearance. Unlike previous works that directly leverage unreliable features extracted from occluded images by off-the-shelf backbones, we propose an occlusion-awareness strategy to handle occlusions for ReID. An occlusion detection module is elaborately designed to generate occlusion-aware feature, which is then used to guide the framework to reason robust appearance and shape features. Extensive experiments demonstrate the superiority of our framework over both cloth-changing Re-ID and occluded Re-ID methods.