Transcription of D DETR: DEFORMABLE TRANSFORMERS FOR -E OBJECT …
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D DETR: DEFORMABLE TRANSFORMERS FOR -E OBJECT …
Published as a conference paper at ICLR 2021. D EFORMABLE DETR: D EFORMABLE T RANSFORMERS. FOR E ND - TO -E ND O BJECT D ETECTION. Xizhou Zhu1 , Weijie Su2 , Lewei Lu1 , Bin Li2 , Xiaogang Wang1,3 , Jifeng Dai1 . 1. SenseTime Research 2. University of Science and Technology of China 3. The Chinese University of Hong Kong [ ] 18 Mar 2021. A BSTRACT. DETR has been recently proposed to eliminate the need for many hand-designed components in OBJECT detection while demonstrating good performance. However, it suffers from slow convergence and limited feature spatial resolution, due to the limitation of Transformer attention modules in processing image feature maps.
Published as a conference paper at ICLR 2021 DEFORMABLE DETR: DEFORMABLE TRANSFORMERS FOR END-TO-END OBJECT DETECTION Xizhou Zhu 1, Weijie Su2z, Lewei Lu , Bin Li2, Xiaogang Wang 1;3, Jifeng Dai y 1SenseTime Research 2University of Science and Technology of China 3The Chinese University of Hong Kong …
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