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DETR has set up a simple end-to-end pipeline for object detection by formulating this task as a set prediction problem, showing promising potential.
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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Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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End-to-end people detection in crowded scenes
Russell Stewart, Mykhaylo Andriluka, and Andrew Y Ng · 2016
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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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End-to-end instance segmentation with recurrent attention
Mengye Ren and Richard S Zemel · 2017
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Recurrent neural networks for semantic instance segmentation
Amaia Salvador, Miriam Bellver, Victor Campos, Manel Baradad, Ferran Marques, Jordi Torres, and Xavier Giro-i Nieto · 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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Acquisition of localization confidence for accurate object detection
Borui Jiang, Ruixuan Luo, Jiayuan Mao, Tete Xiao, and Yuning Jiang · 2018
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2019
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Freeanchor: Learning to match anchors for visual object detection
Xiaosong Zhang, Fang Wan, Chang Liu, Rongrong Ji, and Qixiang Ye · 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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Probabilistic anchor assignment with iou prediction for object detection
Kang Kim and Hee Seok Lee · 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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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
Cited alongside, same era.
Autoassign: Differentiable label assignment for dense object detection
Benjin Zhu, Jianfeng Wang, Zhengkai Jiang, Fuhang Zong, Songtao Liu, Zeming Li, and Jian Sun · 2020
Cited alongside, same era.
Per-pixel classification is not all you need for semantic segmentation
Bowen Cheng, Alex Schwing, and Alexander Kirillov · 2021
Cited alongside, same era.
Solq: Segmenting objects by learning queries
Bin Dong, Fangao Zeng, Tiancai Wang, Xiangyu Zhang, and Yichen Wei · 2021
Cited alongside, same era.
Tood: Task-aligned one-stage object detection
Chengjian Feng, Yujie Zhong, Yu Gao, Matthew R Scott, and Weilin Huang · 2021
Cited alongside, same era.
Adamixer: A fast-converging query-based object detector
Ziteng Gao, Limin Wang, Bing Han, and Sheng Guo · 2022
Later among the works it cites.
Dˆ 2etr: Decoder-only detr with computationally efficient cross-scale attention
Junyu Lin, Xiaofeng Mao, Yuefeng Chen, Lei Xu, Yuan He, and Hui Xue · 2022
Later among the works it cites.
Accelerating detr convergence via semantic-aligned matching
Gongjie Zhang, Zhipeng Luo, Yingchen Yu, Kaiwen Cui, and Shijian Lu · 2022
Later among the works it cites.
Group detr: Fast detr training with group-wise one-to-many assignment
Qiang Chen, Xiaokang Chen, Jian Wang, Shan Zhang, Kun Yao, Haocheng Feng, Junyu Han, Errui Ding, Gang Zeng, and Jingdong Wang · 2023
Closest in time.
Detrs with hybrid matching
Ding Jia, Yuhui Yuan, Haodi He, Xiaopei Wu, Haojun Yu, Weihong Lin, Lei Sun, Chao Zhang, and Han Hu · 2023
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Detection transformer with stable matching
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Zheng Ge, Songtao Liu, Feng Wang, Zeming Li, and Jian Sun · 2021
Cited alongside, same era.
Conditional detr for fast training convergence
Depu Meng, Xiaokang Chen, Zejia Fan, Gang Zeng, Houqiang Li, Yuhui Yuan, Lei Sun, and Jingdong Wang · 2021
Cited alongside, same era.
An end-to-end transformer model for 3d object detection
Ishan Misra, Rohit Girdhar, and Armand Joulin · 2021
Cited alongside, same era.
Sparse r-cnn: End-to-end object detection with learnable proposals
Peize Sun, Rufeng Zhang, Yi Jiang, Tao Kong, Chenfeng Xu, Wei Zhan, Masayoshi Tomizuka, Lei Li, Zehuan Yuan, Changhu Wang, et al · 2021
Cited alongside, same era.
Pnp-detr: Towards efficient visual analysis with transformers
Tao Wang, Li Yuan, Yunpeng Chen, Jiashi Feng, and Shuicheng Yan · 2021
Cited alongside, same era.
Efficient detr: improving end-to-end object detector with dense prior
Zhuyu Yao, Jiangbo Ai, Boxun Li, and Chi Zhang · 2021
Cited alongside, same era.
Varifocalnet: An iou-aware dense object detector
Haoyang Zhang, Ying Wang, Feras Dayoub, and Niko Sunderhauf · 2021
Cited alongside, same era.
Shilong Liu, Tianhe Ren, Jiayu Chen, Zhaoyang Zeng, Hao Zhang, Feng Li, Hongyang Li, Jun Huang, Hang Su, Jun Zhu, et al · 2023
Closest in time.
Rank-detr for high quality object detection
Yifan Pu, Weicong Liang, Yiduo Hao, Yuhui Yuan, Yukang Yang, Chao Zhang, Han Hu, and Gao Huang · 2023
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detrex: Benchmarking detection transformers, 2023
Tianhe Ren, Shilong Liu, Feng Li, Hao Zhang, Ailing Zeng, Jie Yang, Xingyu Liao, Ding Jia, Hongyang Li, He Cao, Jianan Wang, Zhaoyang Zeng, Xianbiao Qi, Yuhui Yuan, Jianwei Yang, and Lei Zhang · 2023
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Cascade-detr: delving into high-quality universal object detection
Mingqiao Ye, Lei Ke, Siyuan Li, Yu-Wing Tai, Chi-Keung Tang, Martin Danelljan, and Fisher Yu · 2023
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Less is more: Focus attention for efficient detr
Dehua Zheng, Wenhui Dong, Hailin Hu, Xinghao Chen, and Yunhe Wang · 2023
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Detrs with collaborative hybrid assignments training
Zhuofan Zong, Guanglu Song, and Yu Liu · 2023
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Salience detr: Enhancing detection transformer with hierarchical salience filtering refinement
Xiuquan Hou, Meiqin Liu, Senlin Zhang, Ping Wei, and Badong Chen · 2024
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Dac-detr: Divide the attention layers and conquer
Zhengdong Hu, Yifan Sun, Jingdong Wang, and Yi Yang · 2024
Closest in time.