Semantic-aligned matching for enhanced DETR convergence and multi-scale feature fusion

Semantic-aligned matching for enhanced DETR convergence and multi-scale feature fusion

The recently proposed DEtection TRansformer (DETR) has established a fully end-to-end paradigm for object detection. However, DETR suffers from slow training convergence, which hinders its applicability to various detection tasks. We observe that DETR’s slow convergence is largely attributed to the...

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Bibliographic Details
Main Authors: Zhang, Gongjie, Luo, Zhipeng, Huang, Jiaxing, Lu, Shijian, Xing, Eric P.
Other Authors: College of Computing and Data Science
Format: Journal Article
Language:English
Published: 2024
Subjects:
Computer and Information Science
Object detection
Vision transformer
Online Access:https://hdl.handle.net/10356/178279

Internet

https://hdl.handle.net/10356/178279

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