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We show that the YOLOv4 object detection neural network based on the CSP approach, scales both up and down and is applicable to small and large networks while maintaining optimal speed and accuracy.
Rich feature hierarchies for accurate object detection and semantic segmentation
Ross Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik · 2014
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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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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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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You only look once: Unified, real-time object detection
Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi · 2016
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Sergey Zagoruyko and Nikos Komodakis · 2016
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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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Densely connected convolutional networks
Gao Huang, Zhuang Liu, Laurens Van Der Maaten, and Kilian Q Weinberger · 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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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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Aggregated residual transformations for deep neural networks
Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, and Kaiming He · 2017
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CornerNet: Detecting objects as paired keypoints
Hei Law and Jia Deng · 2018
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Path aggregation network for instance segmentation
Shu Liu, Lu Qi, Haifang Qin, Jianping Shi, and Jiaya Jia · 2018
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ShuffleNetV2: Practical guidelines for efficient cnn architecture design
Ningning Ma, Xiangyu Zhang, Hai-Tao Zheng, and Jian Sun · 2018
Cited alongside, same era.
YOLOv3: An incremental improvement
Joseph Redmon and Ali Farhadi · 2018
Cited alongside, same era.
Once-for-all: Train one network and specialize it for efficient deployment
Han Cai, Chuang Gan, Tianzhe Wang, Zhekai Zhang, and Song Han · 2019
Cited alongside, same era.
HarDNet: A low memory traffic network
Ping Chao, Chao-Yang Kao, Yu-Shan Ruan, Chien-Hsiang Huang, and Youn-Long Lin · 2019
Cited alongside, same era.
SpineNet: Learning scale-permuted backbone for recognition and localization
Xianzhi Du, Tsung-Yi Lin, Pengchong Jin, Golnaz Ghiasi, Mingxing Tan, Yin Cui, Quoc V Le, and Xiaodan Song · 2019
Cited alongside, same era.
YOLOv4: Optimal speed and accuracy of object detection
Alexey Bochkovskiy, Chien-Yao Wang, and Hong-Yuan Mark Liao · 2020
Closest in time.
D2Det: Towards high quality object detection and instance segmentation
Jiale Cao, Hisham Cholakkal, Rao Muhammad Anwer, Fahad Shahbaz Khan, Yanwei Pang, and Ling Shao · 2020
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CenterMask: Real-time anchor-free instance segmentation
Youngwan Lee and Jongyoul Park · 2020
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PP-YOLO: An effective and efficient implementation of object detector
Xiang Long, Kaipeng Deng, Guanzhong Wang, Yang Zhang, Qingqing Dang, Yuan Gao, Hui Shen, Jianguo Ren, Shumin Han, Errui Ding, et al · 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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CenterNet: Keypoint triplets for object detection
Kaiwen Duan, Song Bai, Lingxi Xie, Honggang Qi, Qingming Huang, and Qi Tian · 2019
Cited alongside, same era.
NAS-FPN: Learning scalable feature pyramid architecture for object detection
Golnaz Ghiasi, Tsung-Yi Lin, and Quoc V Le · 2019
Cited alongside, same era.
CornerNet-Lite: Efficient keypoint based object detection
Hei Law, Yun Teng, Olga Russakovsky, and Jia Deng · 2019
Cited alongside, same era.
An energy and GPU-computation efficient backbone network for real-time object detection
Youngwan Lee, Joong-won Hwang, Sangrok Lee, Yuseok Bae, and Jongyoul Park · 2019
Cited alongside, same era.
Learning spatial fusion for single-shot object detection
Songtao Liu, Di Huang, and Yunhong Wang · 2019
Cited alongside, same era.
ThunderNet: Towards real-time generic object detection
Zheng Qin, Zeming Li, Zhaoning Zhang, Yiping Bao, Gang Yu, Yuxing Peng, and Jian Sun · 2019
Cited alongside, same era.
EfficientNet: Rethinking model scaling for convolutional neural networks
Mingxing Tan and Quoc V Le · 2019
Cited alongside, same era.
Closest in time.
BorderDet: Border feature for dense object detection
Han Qiu, Yuchen Ma, Zeming Li, Songtao Liu, and Jian Sun · 2020
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Designing network design spaces
Ilija Radosavovic, Raj Prateek Kosaraju, Ross Girshick, Kaiming He, and Piotr Dollár · 2020
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Revisiting the sibling head in object detector
Guanglu Song, Yu Liu, and Xiaogang Wang · 2020
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EfficientDet: Scalable and efficient object detection
Mingxing Tan, Ruoming Pang, and Quoc V Le · 2020
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CSPNet: A new backbone that can enhance learning capability of CNN
Chien-Yao Wang, Hong-Yuan Mark Liao, Yueh-Hua Wu, Ping-Yang Chen, Jun-Wei Hsieh, and I-Hau Yeh · 2020
Closest in time.
Side-aware boundary localization for more precise object detection
Jiaqi Wang, Wenwei Zhang, Yuhang Cao, Kai Chen, Jiangmiao Pang, Tao Gong, Jianping Shi, Chen Change Loy, and Dahua Lin · 2020
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Scale-equalizing pyramid convolution for object detection
Xinjiang Wang, Shilong Zhang, Zhuoran Yu, Litong Feng, and Wayne Zhang · 2020
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SM-NAS: Structural-to-modular neural architecture search for object detection
Lewei Yao, Hang Xu, Wei Zhang, Xiaodan Liang, and Zhenguo Li · 2020
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Dynamic R-CNN: Towards high quality object detection via dynamic training
Hongkai Zhang, Hong Chang, Bingpeng Ma, Naiyan Wang, and Xilin Chen · 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
Closest in time.