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Although detection with Transformer (DETR) is increasingly popular, its global attention modeling requires an extremely long training period to optimize and achieve promising detection performance.
The hungarian method for the assignment problem
Harold W Kuhn · 1955
Earlier work this paper cites.
Rich feature hierarchies for accurate object detection and semantic segmentation
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Microsoft coco: Common objects in context
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Very deep convolutional networks for large-scale image recognition
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Object detection via a multi-region and semantic segmentation-aware cnn model
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Fast r-cnn
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Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton · 2016
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Attend refine repeat: Active box proposal generation via in-out localization
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Craft objects from images
Bin Yang, Junjie Yan, Zhen Lei, and Stan Z Li · 2016
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Deformable convolutional networks
Jifeng Dai, Haozhi Qi, Yuwen Xiong, Yi Li, Guodong Zhang, Han Hu, and Yichen Wei · 2017
Earlier work this paper cites.
Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
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Feature pyramid networks for object detection
Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie · 2017
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Focal loss for dense object detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Aggregated residual transformations for deep neural networks
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Context refinement for object detection
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Squeeze-and-excitation networks
Jie Hu, Li Shen, and Gang Sun · 2018
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Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, and Jifeng Dai · 2020
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A shape transformation-based dataset augmentation framework for pedestrian detection
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Stand-alone self-attention in vision models
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