Salience DETR: Enhancing Detection Transformer with Hierarchical Salience Filtering Refinement

arXiv:2403.16131v1 Announce Type: new
Abstract: DETR-like methods have significantly increased detection performance in an end-to-end manner. The mainstream two-stage frameworks of them perform dense self-attention and select a fraction of queries for sparse cross-attention, which is proven effective for improving performance but also introduces a heavy computational burden and high dependence on stable query selection. This paper demonstrates that suboptimal two-stage selection strategies result in scale bias and redundancy due to the mismatch between selected queries and objects in two-stage …

arxiv cs.cv detection detection transformer detr filtering hierarchical transformer type