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Detection Transformer (DETR) directly transforms queries to unique objects by using one-to-one bipartite matching during training and enables end-to-end object detection.
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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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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You only look once: Unified, real-time object detection
Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi · 2016
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Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 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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YOLO9000: better, faster, stronger
Joseph Redmon and Ali Farhadi · 2017
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Cascade r-cnn: Delving into high quality object detection
Zhaowei Cai and Nuno Vasconcelos · 2018
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Yolov3: An incremental improvement
Joseph Redmon and Ali Farhadi · 2018
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Crowdhuman: A benchmark for detecting human in a crowd
Shuai Shao, Zijian Zhao, Boxun Li, Tete Xiao, Gang Yu, Xiangyu Zhang, and Jian Sun · 2018
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Hybrid task cascade for instance segmentation
Kai Chen, Jiangmiao Pang, Jiaqi Wang, Yu Xiong, Xiaoxiao Li, Shuyang Sun, Wansen Feng, Ziwei Liu, Jianping Shi, Wanli Ouyang, et al · 2019
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A solution for densely annotated large scale object detection task
Yuan Gao, Hui Shen, Donghong Zhong, Jian Wang, Zeyu Liu, Ti Bai, Xiang Long, and Shilei Wen · 2019
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LVIS: A dataset for large vocabulary instance segmentation
Agrim Gupta, Piotr Dollar, and Ross Girshick · 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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Detectron2
Yuxin Wu, Alexander Kirillov, Francisco Massa, Wan-Yen Lo, and Ross Girshick · 2019
Cited alongside, same era.
Xingyi Zhou, Dequan Wang, and Philipp Krähenbühl · 2019
Cited alongside, same era.
End-to-end object detection with transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
Cited alongside, same era.
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
Cited alongside, same era.
Efficientdet: Scalable and efficient object detection
Mingxing Tan, Ruoming Pang, and Quoc V Le · 2020
Cited alongside, same era.
Bridging the gap between anchor-based and anchor-free detection via adaptive training sample selection
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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Rethinking transformer-based set prediction for object detection
Zhiqing Sun, Shengcao Cao, Yiming Yang, and Kris Kitani · 2021
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Scaled-YOLOv4: Scaling Cross Stage Partial Network
Chien-Yao Wang, Alexey Bochkovskiy, and Hong-Yuan Mark Liao · 2021
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Anchor detr: Query design for transformer-based detector
Yingming Wang, Xiangyu Zhang, Tong Yang, and Jian Sun · 2021
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Efficient DETR: Improving End-to-End Object Detector with Dense Prior
Zhuyu Yao, Jiangbo Ai, Boxun Li, and Chi Zhang · 2021
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Shifeng Zhang, Cheng Chi, Yongqiang Yao, Zhen Lei, and Stan Z Li · 2020
Cited alongside, same era.
You only look one-level feature
Qiang Chen, Yingming Wang, Tong Yang, Xiangyu Zhang, Jian Cheng, and Jian Sun · 2021
Cited alongside, same era.
Per-Pixel Classification is Not All You Need for Semantic Segmentation
Bowen Cheng, Alexander G. Schwing, and Alexander Kirillov · 2021
Cited alongside, same era.
Dynamic head: Unifying object detection heads with attentions
Xiyang Dai, Yinpeng Chen, Bin Xiao, Dongdong Chen, Mengchen Liu, Lu Yuan, and Lei Zhang · 2021
Cited alongside, same era.
Up-detr: Unsupervised pre-training for object detection with transformers
Zhigang Dai, Bolun Cai, Yugeng Lin, and Junying Chen · 2021
Cited alongside, same era.
Simple copy-paste is a strong data augmentation method for instance segmentation
Golnaz Ghiasi, Yin Cui, Aravind Srinivas, Rui Qian, Tsung-Yi Lin, Ekin D Cubuk, Quoc V Le, and Barret Zoph · 2021
Cited alongside, same era.
Generalized Focal Loss V2: Learning Reliable Localization Quality Estimation for Dense Object Detection
Xiang Li, Wenhai Wang, Xiaolin Hu, Jun Li, Jinhui Tang, and Jian Yang · 2021
Cited alongside, same era.
Xingyi Zhou, Vladlen Koltun, and Philipp Krähenbühl · 2021
Later among the works it cites.
Deformable DETR: Deformable Transformers for End-to-End Object Detection
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, and Jifeng Dai · 2021
Later among the works it cites.
Group detr: Fast training convergence with decoupled one-to-many label assignment
Qiang Chen, Xiaokang Chen, Gang Zeng, and Jingdong Wang · 2022
Closest in time.
Ding Jia, Yuhui Yuan, Haodi He, Xiaopei Wu, Haojun Yu, Weihong Lin, Lei Sun, Chao Zhang, and Han Hu · 2022
Closest in time.
DN-DETR: Accelerate DETR Training by Introducing Query DeNoising
Feng Li, Hao Zhang, Shilong Liu, Jian Guo, Lionel M Ni, and Lei Zhang · 2022
Closest in time.
DAB-DETR: Dynamic anchor boxes are better queries for DETR
Shilong Liu, Feng Li, Hao Zhang, Xiao Yang, Xianbiao Qi, Hang Su, Jun Zhu, and Lei Zhang · 2022
Closest in time.
Fqdet: Fast-converging query-based detector
Cédric Picron, Punarjay Chakravarty, and Tinne Tuytelaars · 2022
Closest in time.
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 · 2022
Closest in time.