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We present a conceptually simple, efficient, and general framework for localization problems in DETR-like models.
The hungarian method for the assignment problem
Harold W Kuhn · 1955
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Diagnosing error in object detectors
Derek Hoiem, Yodsawalai Chodpathumwan, and Qieyun Dai · 2012
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Rich feature hierarchies for accurate object detection and semantic segmentation
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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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Object detection via a multi-region and semantic segmentation-aware cnn model
Spyros Gidaris and Nikos Komodakis · 2015
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Fast r-cnn
Ross Girshick · 2015
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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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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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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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Cascade r-cnn: Delving into high quality object detection
Zhaowei Cai and Nuno Vasconcelos · 2018
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Decoupled classification refinement: Hard false positive suppression for object detection
Bowen Cheng, Yunchao Wei, Rogerio Feris, Jinjun Xiong, Wen-mei Hwu, Thomas Huang, and Humphrey Shi · 2018
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Revisiting rcnn: On awakening the classification power of faster rcnn
Bowen Cheng, Yunchao Wei, Honghui Shi, Rogerio Feris, Jinjun Xiong, and Thomas Huang · 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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Learning efficient single-stage pedestrian detectors by asymptotic localization fitting
Wei Liu, Shengcai Liao, Weidong Hu, Xuezhi Liang, and Xiao Chen · 2018
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Failing to learn: Autonomously identifying perception failures for self-driving cars
Manikandasriram Srinivasan Ramanagopal, Cyrus Anderson, Ram Vasudevan, and Matthew Johnson-Roberson · 2018
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Lvis: A dataset for large vocabulary instance segmentation
Agrim Gupta, Piotr Dollar, and Ross Girshick · 2019
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Scale-aware trident networks for object detection
Yanghao Li, Yuntao Chen, Naiyan Wang, and Zhaoxiang Zhang · 2019
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Grid r-cnn
Xin Lu, Buyu Li, Yuxin Yue, Quanquan Li, and Junjie Yan · 2019
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Libra r-cnn: Towards balanced learning for object detection
Jiangmiao Pang, Kai Chen, Jianping Shi, Huajun Feng, Wanli Ouyang, and Dahua Lin · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
Introspective false negative prediction for black-box object detectors in autonomous driving
Qinghua Yang, Hui Chen, Zhe Chen, and Junzhe Su · 2021
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Probabilistic two-stage detection
Xingyi Zhou, Vladlen Koltun, and Philipp Krähenbühl · 2021
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Group detr: Fast training convergence with decoupled one-to-many label assignment
Qiang Chen, Xiaokang Chen, Gang Zeng, and Jingdong Wang · 2022
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Group detr v2: Strong object detector with encoder-decoder pretraining
Qiang Chen, Jian Wang, Chuchu Han, Shan Zhang, Zexian Li, Xiaokang Chen, Jiahui Chen, Xiaodi Wang, Shuming Han, Gang Zhang, et al · 2022
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detrex: An research platform for transformer-based object detection algorithms
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Did you miss the sign? a false negative alarm system for traffic sign detectors
Quazi Marufur Rahman, Niko Sünderhauf, and Feras Dayoub · 2019
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Generalized intersection over union: A metric and a loss for bounding box regression
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Detectron2
Yuxin Wu, Alexander Kirillov, Francisco Massa, Wan-Yen Lo, and Ross Girshick · 2019
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Tide: A general toolbox for identifying object detection errors
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End-to-end object detection with transformers
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Single-shot bidirectional pyramid networks for high-quality object detection
Xiongwei Wu, Doyen Sahoo, Daoxin Zhang, Jianke Zhu, and Steven CH Hoi · 2020
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detrex contributors · 2022
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F-vlm: Open-vocabulary object detection upon frozen vision and language models
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Dn-detr: Accelerate detr training by introducing query denoising
Feng Li, Hao Zhang, Shilong Liu, Jian Guo, Lionel M Ni, and Lei Zhang · 2022
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Million-scale object detection with large vision model
Feng Lin, Wenze Hu, Yaowei Wang, Yonghong Tian, Guangming Lu, Fanglin Chen, Yong Xu, and Xiaoyu Wang · 2022
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Could giant pretrained image models extract universal representations?
Yutong Lin, Ze Liu, Zheng Zhang, Han Hu, Nanning Zheng, Stephen Lin, and Yue Cao · 2022
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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
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Why object detectors fail: Investigating the influence of the dataset
Dimity Miller, Georgia Goode, Callum Bennie, Peyman Moghadam, and Raja Jurdak · 2022
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What’s in the black box? the false negative mechanisms inside object detectors
Dimity Miller, Peyman Moghadam, Mark Cox, Matt Wildie, and Raja Jurdak · 2022
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Jeffrey Ouyang-Zhang, Jang Hyun Cho, Xingyi Zhou, and Philipp Krähenbühl · 2022
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Proper reuse of image classification features improves object detection
Cristina Vasconcelos, Vighnesh Birodkar, and Vincent Dumoulin · 2022
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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 Ni, and Harry Shum · 2022
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Detrs with collaborative hybrid assignments training
Zhuofan Zong, Guanglu Song, and Yu Liu · 2022
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