학술논문

Occluded Cloth-Changing Person Re-Identification via Occlusion-aware Appearance and Shape Reasoning
Document Type
Conference
Source
2024 IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) Advanced Video and Signal Based Surveillance (AVSS), 2024 IEEE International Conference on. :1-8 Jul, 2024
Subject
Computing and Processing
Signal Processing and Analysis
Couplings
Computer vision
Shape
Surveillance
Clothing
Feature extraction
Transformers
Language
ISSN
2643-6213
Abstract
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.