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Modern detection transformers (DETRs) use a set of object queries to predict a list of bounding boxes, sort them by their classification confidence scores, and select the top-ranked predictions as the final detection results for the given input image.
Microsoft COCO: Common Objects in Context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C. Lawrence Zitnick · 2014
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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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Multi-scale dense networks for resource efficient image classification
Gao Huang, Danlu Chen, Tianhong Li, Felix Wu, Laurens Van Der Maaten, and Kilian Q Weinberger · 2018
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Acquisition of localization confidence for accurate object detection
Borui Jiang, Ruixuan Luo, Jiayuan Mao, Tete Xiao, and Yuning Jiang · 2018
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Neural speed reading with structural-jump-lstm
Christian Hansen, Casper Hansen, Stephen Alstrup, Jakob Grue Simonsen, and Christina Lioma · 2019
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Fcos: Fully convolutional one-stage object detection
Zhi Tian, Chunhua Shen, Hao Chen, and Tong He · 2019
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End-to-end object detection with transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
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AP-loss for accurate one-stage object detection
Kean Chen, Weiyao Lin, Jianguo Li, John See, Ji Wang, and Junni Zou · 2020
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Generalized focal loss: Learning qualified and distributed bounding boxes for dense object detection
Xiang Li, Wenhai Wang, Lijun Wu, Shuo Chen, Xiaolin Hu, Jun Li, Jinhui Tang, and Jian Yang · 2020
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DETR for crowd pedestrian detection
Matthieu Lin, Chuming Li, Xingyuan Bu, Ming Sun, Chen Lin, Junjie Yan, Wanli Ouyang, and Zhidong Deng · 2020
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A ranking-based, balanced loss function unifying classification and localisation in object detection
Kemal Oksuz, Baris Can Cam, Emre Akbas, and Sinan Kalkan · 2020
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DR loss: Improving object detection by distributional ranking
Qi Qian, Lei Chen, Hao Li, and Rong Jin · 2020
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Transtrack: Multiple object tracking with transformer
Peize Sun, Jinkun Cao, Yi Jiang, Rufeng Zhang, Enze Xie, Zehuan Yuan, Changhu Wang, and Ping Luo · 2020
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Object-contextual representations for semantic segmentation
Yuhui Yuan, Xilin Chen, and Jingdong Wang · 2020
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Bridging the gap between anchor-based and anchor-free detection via adaptive training sample selection
Shifeng Zhang, Cheng Chi, Yongqiang Yao, Zhen Lei, and Stan Z Li · 2020
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Transformer tracking
Xin Chen, Bin Yan, Jiawen Zhu, Dong Wang, Xiaoyun Yang, and Huchuan Lu · 2021
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Dynamic DETR: End-to-end object detection with dynamic attention
Xiyang Dai, Yinpeng Chen, Jianwei Yang, Pengchuan Zhang, Lu Yuan, and Lei Zhang · 2021
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SOLQ: Segmenting objects by learning queries
Bin Dong, Fangao Zeng, Tiancai Wang, Xiangyu Zhang, and Yichen Wei · 2021
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Instances as queries
Yuxin Fang, Shusheng Yang, Xinggang Wang, Yu Li, Chen Fang, Ying Shan, Bin Feng, and Wenyu Liu · 2021
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TOOD: Task-aligned one-stage object detection
Chengjian Feng, Yujie Zhong, Yu Gao, Matthew R Scott, and Weilin Huang · 2021
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Fast convergence of detr with spatially modulated co-attention
Peng Gao, Minghang Zheng, Xiaogang Wang, Jifeng Dai, and Hongsheng Li · 2021
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Dynamic neural networks: A survey
Yizeng Han, Gao Huang, Shiji Song, Le Yang, Honghui Wang, and Yulin Wang · 2021
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Spatially adaptive feature refinement for efficient inference
Yizeng Han, Gao Huang, Shiji Song, Le Yang, Yitian Zhang, and Haojun Jiang · 2021
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Pose recognition with cascade transformers
Ke Li, Shijie Wang, Xiang Zhang, Yifan Xu, Weijian Xu, and Zhuowen Tu · 2021
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Conditional DETR for fast training convergence
Depu Meng, Xiaokang Chen, Zejia Fan, Gang Zeng, Houqiang Li, Yuhui Yuan, Lei Sun, and Jingdong Wang · 2021
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Rank & sort loss for object detection and instance segmentation
Kemal Oksuz, Baris Can Cam, Emre Akbas, and Sinan Kalkan · 2021
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End-to-end trainable multi-instance pose estimation with transformers
Lucas Stoffl, Maxime Vidal, and Alexander Mathis · 2021
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Huiyu Wang, Yukun Zhu, Hartwig Adam, Alan Yuille, and Liang-Chieh Chen · 2021
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Glancing at the patch: Anomaly localization with global and local feature comparison
Shenzhi Wang, Liwei Wu, Lei Cui, and Yujun Shen · 2021
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Adaptive focus for efficient video recognition
Yulin Wang, Zhaoxi Chen, Haojun Jiang, Shiji Song, Yizeng Han, and Gao Huang · 2021
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Not all images are worth 16x16 words: Dynamic transformers for efficient image recognition
Yulin Wang, Rui Huang, Shiji Song, Zeyi Huang, and Gao Huang · 2021
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Camouflaged object detection with feature decomposition and edge reconstruction
Chunming He, Kai Li, Yachao Zhang, Longxiang Tang, Yulun Zhang, Zhenhua Guo, and Xiu Li · 2023
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VarifocalNet: An iou-aware dense object detector
Haoyang Zhang, Ying Wang, Feras Dayoub, and Niko Sunderhauf · 2021
Cited alongside, same era.
Deformable DETR: Deformable transformers for end-to-end object detection
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, and Jifeng Dai · 2021
Cited alongside, same era.
CF-DETR: Coarse-to-fine transformers for end-to-end object detection
Xipeng Cao, Peng Yuan, Bailan Feng, Kun Niu, and Yao Zhao · 2022
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Masked-attention mask transformer for universal image segmentation
Bowen Cheng, Ishan Misra, Alexander G Schwing, Alexander Kirillov, and Rohit Girdhar · 2022
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Adamixer: A fast-converging query-based object detector
Ziteng Gao, Limin Wang, Bing Han, and Sheng Guo · 2022
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Learning to weight samples for dynamic early-exiting networks
Yizeng Han, Yifan Pu, Zihang Lai, Chaofei Wang, Shiji Song, Junfen Cao, Wenhui Huang, Chao Deng, and Gao Huang · 2022
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Latency-aware spatial-wise dynamic networks
Yizeng Han, Zhihang Yuan, Yifan Pu, Chenhao Xue, Shiji Song, Guangyu Sun, and Gao Huang · 2022
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Joint representation learning for text and 3d point cloud
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DETRs with hybrid matching
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Mask frozen-detr: High quality instance segmentation with one gpu
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Detr does not need multi-scale or locality design
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Detection transformer with stable matching
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Fine-grained recognition with learnable semantic data augmentation
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Adaptive rotated convolution for rotated object detection
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detrex: Benchmarking detection transformers
Tianhe Ren, Shilong Liu, Feng Li, Hao Zhang, Ailing Zeng, Jie Yang, Xingyu Liao, Ding Jia, Hongyang Li, He Cao, et al · 2023
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V-detr: Detr with vertex relative position encoding for 3d object detection
Yichao Shen, Zigang Geng, Yuhui Yuan, Yutong Lin, Ze Liu, Chunyu Wang, Han Hu, Nanning Zheng, and Baining Guo · 2023
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Computation-efficient deep learning for computer vision: A survey
Yulin Wang, Yizeng Han, Chaofei Wang, Shiji Song, Qi Tian, and Gao Huang · 2023
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Boosting offline reinforcement learning with action preference query
Qisen Yang, Shenzhi Wang, Matthieu Gaetan Lin, Shiji Song, and Gao Huang · 2023
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Hundreds guide millions: Adaptive offline reinforcement learning with expert guidance
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Offline prioritized experience replay
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Value-consistent representation learning for data-efficient reinforcement learning
Yang Yue, Bingyi Kang, Zhongwen Xu, Gao Huang, and Shuicheng Yan · 2023
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DINO: DETR with improved denoising anchor boxes for end-to-end object detection
Hao Zhang, Feng Li, Shilong Liu, Lei Zhang, Hang Su, Jun Zhu, Lionel M Ni, and Heung-Yeung Shum · 2023
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