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Benchmarks, such as COCO, play a crucial role in object detection.
EfficientDet: Scalable and efficient object detection
Mingxing Tan, Ruoming Pang, and Quoc V. Le · 1911
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Neural network-based face detection
Henry A. Rowley, Shumeet Baluja, and Takeo Kanade · 1998
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2nd place solution for Waymo Open Dataset challenge – 2D object detection
Sijia Chen, Yu Wang, Li Huang, Runzhou Ge, Yihan Hu, Zhuangzhuang Ding, and Jie Liao · 2006
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Pedestrian detection: An evaluation of the state of the art
Piotr Dollár, Christian Wojek, Bernt Schiele, and Pietro Perona · 2012
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Are we ready for autonomous driving? the KITTI vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
Earlier work this paper cites.
Diagnosing error in object detectors
Derek Hoiem, Yodsawalai Chodpathumwan, and Qieyun Dai · 2012
Earlier work this paper cites.
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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The PASCAL Visual Object Classes challenge: A retrospective
Mark Everingham, S. M. Ali Eslami, Luc Van Gool, Christopher K. I. Williams, John Winn, and Andrew Zisserman · 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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ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael S. Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Shallow networks for high-accuracy road object-detection
Khalid Ashraf, Bichen Wu, Forrest N. Iandola, Mattthew W. Moskewicz, and Kurt Keutzer · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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SSD: Single shot multibox detector
Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, and Alexander C. Berg · 2016
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Rethinking the inception architecture for computer vision
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, and Zbigniew Wojna · 2016
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WIDER FACE: A face detection benchmark
Shuo Yang, Ping Luo, Chen-Change Loy, and Xiaoou Tang · 2016
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Soft-NMS – improving object detection with one line of code
Navaneeth Bodla, Bharat Singh, Rama Chellappa, and Larry S. Davis · 2017
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Deformable convolutional networks
Jifeng Dai, Haozhi Qi, Yuwen Xiong, Yi Li, Guodong Zhang, Han Hu, and Yichen Wei · 2017
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DSSD : Deconvolutional single shot detector
Cheng-Yang Fu, Wei Liu, Ananth Ranga, Ambrish Tyagi, and Alexander C. Berg · 2017
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Speed/accuracy trade-offs for modern convolutional object detectors
Jonathan Huang, Vivek Rathod, Chen Sun, Menglong Zhu, Anoop Korattikara, Alireza Fathi, Ian Fischer, Zbigniew Wojna, Yang Song, Sergio Guadarrama, and Kevin Murphy · 2017
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Driving in the matrix: Can virtual worlds replace human-generated annotations for real world tasks?
Matthew Johnson-Roberson, Charles Barto, Rounak Mehta, Sharath Nittur Sridhar, Karl Rosaen, and Ram Vasudevan · 2017
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Sketch-based manga retrieval using Manga109 dataset
Yusuke Matsui, Kota Ito, Yuji Aramaki, Azuma Fujimoto, Toru Ogawa, Toshihiko Yamasaki, and Kiyoharu Aizawa · 2017
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Aggregated residual transformations for deep neural networks
Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, and Kaiming He · 2017
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Cascade R-CNN: Delving into high quality object detection
Zhaowei Cai and Nuno Vasconcelos · 2018
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Detectron
Ross Girshick, Ilija Radosavovic, Georgia Gkioxari, Piotr Dollár, and Kaiming He · 2018
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Cross-domain weakly-supervised object detection through progressive domain adaptation
Naoto Inoue, Ryosuke Furuta, Toshihiko Yamasaki, and Kiyoharu Aizawa · 2018
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Object detection for comics using Manga109 annotations
Toru Ogawa, Atsushi Otsubo, Rei Narita, Yusuke Matsui, Toshihiko Yamasaki, and Kiyoharu Aizawa · 2018
Cited alongside, same era.
MegDet: A large mini-batch object detector
Chao Peng, Tete Xiao, Zeming Li, Yuning Jiang, Xiangyu Zhang, Kai Jia, Gang Yu, and Jian Sun · 2018
Cited alongside, same era.
An analysis of scale invariance in object detection – SNIP
Bharat Singh and Larry S. Davis · 2018
Cited alongside, same era.
Between-class learning for image classification
Yuji Tokozume, Yoshitaka Ushiku, and Tatsuya Harada · 2018
Cited alongside, same era.
mixup: Beyond empirical risk minimization
Hongyi Zhang, Moustapha Cisse, Yann N. Dauphin, and David Lopez-Paz · 2018
Cited alongside, same era.
Towards Universal Object Detection
Zhaowei Cai · 2019
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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COCO API
Tsung-Yi Lin, Piotr Dollár, et al · 2020
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Deep learning for generic object detection: A survey
Li Liu, Wanli Ouyang, Xiaogang Wang, Paul Fieguth, Jie Chen, Xinwang Liu, and Matti Pietikäinen · 2020
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A metric learning reality check
Kevin Musgrave, Serge Belongie, and Ser-Nam Lim · 2020
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DetectoRS: Detecting objects with recursive feature pyramid and switchable atrous convolution
Siyuan Qiao, Liang-Chieh Chen, and Alan Yuille · 2020
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Green AI
Roy Schwartz, Jesse Dodge, Noah A. Smith, and Oren Etzioni · 2020
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Cited alongside, same era.
MMDetection: Open mmlab detection toolbox and benchmark
Kai Chen, Jiaqi Wang, Jiangmiao Pang, Yuhang Cao, Yu Xiong, Xiaoxiao Li, Shuyang Sun, Wansen Feng, Ziwei Liu, Jiarui Xu, Zheng Zhang, Dazhi Cheng, Chenchen Zhu, Tianheng Cheng, Qijie Zhao, Buyu Li, Xin Lu, Rui Zhu, Yue Wu, Jifeng Dai, Jingdong Wang, Jianping Shi, Wanli Ouyang, Chen Change Loy, and Dahua Lin · 2019
Cited alongside, same era.
LVIS: A dataset for large vocabulary instance segmentation
Agrim Gupta, Piotr Dollár, and Ross Girshick · 2019
Cited alongside, same era.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2019
Cited alongside, same era.
Objects365: A large-scale, high-quality dataset for object detection
Shuai Shao, Zeming Li, Tianyuan Zhang, Chao Peng, Gang Yu, Xiangyu Zhang, Jing Li, and Jian Sun · 2019
Cited alongside, same era.
Understanding the effects of pre-training for object detectors via eigenspectrum
Yosuke Shinya, Edgar Simo-Serra, and Taiji Suzuki · 2019
Cited alongside, same era.
EfficientNet: Rethinking model scaling for convolutional neural networks
Mingxing Tan and Quoc V. Le · 2019
Cited alongside, same era.
Later among the works it cites.
Revisiting the sibling head in object detector
Guanglu Song, Yu Liu, and Xiaogang Wang · 2020
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Scalability in perception for autonomous driving: Waymo Open Dataset
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, Vijay Vasudevan, Wei Han, Jiquan Ngiam, Hang Zhao, Aleksei Timofeev, Scott Ettinger, Maxim Krivokon, Amy Gao, Aditya Joshi, Yu Zhang, Jonathon Shlens, Zhifeng Chen, and Dragomir Anguelov · 2020
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Data augmentation using random image cropping and patching for deep CNNs
Ryo Takahashi, Takashi Matsubara, and Kuniaki Uehara · 2020
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SPNAS-Noah: Single Cascade-RCNN with backbone architecture adaption for Waymo 2D detection
Hang Xu, Chenhan Jiang, Dapeng Feng, Chaoqiang Ye, Rui Sun, and Xiaodan Liang · 2020
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Scale match for tiny person detection
Xuehui Yu, Yuqi Gong, Nan Jiang, Qixiang Ye, and Zhenjun Han · 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
Later among the works it cites.
Object detection with a unified label space from multiple datasets
Xiangyun Zhao, Samuel Schulter, Gaurav Sharma, Yi-Hsuan Tsai, Manmohan Chandraker, and Ying Wu · 2020
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Dynamic head: Unifying object detection heads with attentions
Xiyang Dai, Yinpeng Chen, Bin Xiao, Dongdong Chen, Mengchen Liu, Lu Yuan, and Lei Zhang · 2021
Closest in time.
Object detection in aerial images: A large-scale benchmark and challenges
Jian Ding, Nan Xue, Gui-Song Xia, Xiang Bai, Wen Yang, Michael Ying Yang, Serge Belongie, Jiebo Luo, Mihai Datcu, Marcello Pelillo, and Liangpei Zhang · 2021
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Res2Net: A new multi-scale backbone architecture
Shang-Hua Gao, Ming-Ming Cheng, Kai Zhao, Xin-Yu Zhang, Ming-Hsuan Yang, and Philip Torr · 2021
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YOLOX: Exceeding YOLO series in 2021
Zheng Ge, Songtao Liu, Feng Wang, Zeming Li, and Jian Sun · 2021
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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
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Swin Transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
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Unsupervised domain adaptation of object detectors: A survey
Poojan Oza, Vishwanath A. Sindagi, Vibashan VS, and Vishal M. Patel · 2021
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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, and Ping Luo · 2021
Closest in time.
A comment about the training log of EfficientDet
Mingxing Tan · 2021
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Deformable DETR: Deformable transformers for end-to-end object detection
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, and Jifeng Dai · 2021
Closest in time.
A convnet for the 2020s
Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, and Saining Xie · 2022
Closest in time.
Simple multi-dataset detection
Xingyi Zhou, Vladlen Koltun, and Philipp Krähenbühl · 2022
Closest in time.