DETRs with Hybrid Matching
Peking University · Microsoft Research Asia (China) · +2 more institutions
Abstract
One-to-one set matching is a key design for DETR to establish its end-to-end capability, so that object detection does not require a hand-crafted NMS (non-maximum suppression) to remove duplicate detections. This end-to-end signature is important for the versatility of DETR, and it has been generalized to broader vision tasks. However, we note that there are few queries assigned as positive samples and the one-to-one set matching significantly reduces the training efficacy of positive samples. We propose a simple yet effective method based on a hybrid matching scheme that combines the original one-to-one matching branch with an auxiliary one-to-many matching branch during training. Our hybrid strategy has been…
Citation impact
- FWCI
- 24.08
- Percentile
- 100%
- References
- 91
Authors
9Topics & keywords
- Matching (statistics)
- Computer science
- Set (abstract data type)
- Inference
- Data mining
- Object (grammar)
- Code (set theory)
- Range (aeronautics)