Holi-DETR: Holistic Fashion Item Detection
Published:Dec 29, 2025 05:55
•1 min read
•ArXiv
Analysis
This paper addresses the challenge of fashion item detection, which is difficult due to the diverse appearances and similarities of items. It proposes Holi-DETR, a novel DETR-based model that leverages contextual information (co-occurrence, spatial arrangements, and body keypoints) to improve detection accuracy. The key contribution is the integration of these diverse contextual cues into the DETR framework, leading to improved performance compared to existing methods.
Key Takeaways
- •Proposes Holi-DETR, a novel DETR-based model for fashion item detection.
- •Leverages contextual information (co-occurrence, spatial arrangements, body keypoints) to improve accuracy.
- •Integrates diverse contextual cues into the DETR framework.
- •Achieves improved performance compared to vanilla DETR and Co-DETR.
Reference
“Holi-DETR explicitly incorporates three types of contextual information: (1) the co-occurrence probability between fashion items, (2) the relative position and size based on inter-item spatial arrangements, and (3) the spatial relationships between items and human body key-points.”