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We aim at providing the object detection community with an efficient and performant object detector, termed YOLO-MS.
MMDetection: Open mmlab detection toolbox and benchmark, 2019
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 · 1906
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Scale-space filtering: A new approach to multi-scale description
Andrew Witkin · 1984
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Yolov4: Optimal speed and accuracy of object detection, 2020
Alexey Bochkovskiy, Chien-Yao Wang, and Hong-Yuan Mark Liao · 2004
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Exponential moving average versus moving exponential average
Frank Klinker · 2010
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Rich feature hierarchies for accurate object detection and semantic segmentation
Ross Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik · 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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Fast r-cnn
Ross Girshick · 2015
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Spatial pyramid pooling in deep convolutional networks for visual recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 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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R-fcn: Object detection via region-based fully convolutional networks
Jifeng Dai, Yi Li, Kaiming He, and Jian Sun · 2016
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Understanding the effective receptive field in deep convolutional neural networks
Wenjie Luo, Yujia Li, Raquel Urtasun, and Richard Zemel · 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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Rethinking atrous convolution for semantic image segmentation, 2017
Liang-Chieh Chen, George Papandreou, Florian Schroff, and Hartwig Adam · 2017
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Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollar, and Ross Girshick · 2017
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Adam: A method for stochastic optimization, 2017
Diederik P. Kingma and Jimmy Ba · 2017
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Feature pyramid networks for object detection
Tsung-Yi Lin, Piotr Dollar, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie · 2017
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Yolo9000: Better, faster, stronger
Joseph Redmon and Ali Farhadi · 2017
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Grad-cam: Visual explanations from deep networks via gradient-based localization
Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz 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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Sigmoid-weighted linear units for neural network function approximation in reinforcement learning
Stefan Elfwing, Eiji Uchibe, and Kenji Doya · 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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Yolov3: An incremental improvement, 2018
Joseph Redmon and Ali Farhadi · 2018
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Mobilenetv2: Inverted residuals and linear bottlenecks
Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, and Liang-Chieh Chen · 2018
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Crowdhuman: A benchmark for detecting human in a crowd, 2018
Shuai Shao, Zijian Zhao, Boxun Li, Tete Xiao, Gang Yu, Xiangyu Zhang, and Jian Sun · 2018
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Dota: A large-scale dataset for object detection in aerial images
Gui-Song Xia, Xiang Bai, Jian Ding, Zhen Zhu, Serge Belongie, Jiebo Luo, Mihai Datcu, Marcello Pelillo, and Liangpei Zhang · 2018
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mixup: Beyond empirical risk minimization
Hongyi Zhang, Moustapha Cisse, Yann N. Dauphin, and David Lopez-Paz · 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, Chen Change Loy, and Dahua Lin · 2019
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Benchmarking single-image dehazing and beyond
Boyi Li, Wenqi Ren, Dengpan Fu, Dacheng Tao, Dan Feng, Wenjun Zeng, and Zhangyang Wang · 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
Segnext: Rethinking convolutional attention design for semantic segmentation
Meng-Hao Guo, Cheng-Ze Lu, Qibin Hou, Zhengning Liu, Ming-Ming Cheng, and Shi-min Hu · 2022
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Attention mechanisms in computer vision: A survey
Meng-Hao Guo, Tian-Xing Xu, Jiang-Jiang Liu, Zheng-Ning Liu, Peng-Tao Jiang, Tai-Jiang Mu, Song-Hai Zhang, Ralph R. Martin, Ming-Ming Cheng, and Shi-Min Hu · 2022
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Transformers in vision: A survey
Salman Khan, Muzammal Naseer, Munawar Hayat, Syed Waqas Zamir, Fahad Shahbaz Khan, and Mubarak Shah · 2022
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Yolov6: A single-stage object detection framework for industrial applications, 2022
Chuyi Li, Lulu Li, Hongliang Jiang, Kaiheng Weng, Yifei Geng, Liang Li, Zaidan Ke, Qingyuan Li, Meng Cheng, Weiqiang Nie, Yiduo Li, Bo Zhang, Yufei Liang, Linyuan Zhou, Xiaoming Xu, Xiangxiang Chu, Xiaoming Wei, and Xiaolin Wei · 2022
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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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Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
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Generalized intersection over union: A metric and a loss for bounding box regression
Hamid Rezatofighi, Nathan Tsoi, JunYoung Gwak, Amir Sadeghian, Ian Reid, and Silvio Savarese · 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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Region proposal by guided anchoring
Jiaqi Wang, Kai Chen, Shuo Yang, Chen Change Loy, and Dahua Lin · 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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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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Focal loss for dense object detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollar · 2020
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Spatial group-wise enhance: Enhancing semantic feature learning in cnn
Yuxuan Li, Xiang Li, and Jian Yang · 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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A convnet for the 2020s
Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, and Saining Xie · 2022
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Rtmdet: An empirical study of designing real-time object detectors, 2022
Chengqi Lyu, Wenwei Zhang, Haian Huang, Yue Zhou, Yudong Wang, Yanyi Liu, Shilong Zhang, and Kai Chen · 2022
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Designing network design strategies through gradient path analysis, 2022
Chien-Yao Wang, Hong-Yuan Mark Liao, and I-Hau Yeh · 2022
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Pp-yoloe: An evolved version of yolo, 2022
Shangliang Xu, Xinxin Wang, Wenyu Lv, Qinyao Chang, Cheng Cui, Kaipeng Deng, Guanzhong Wang, Qingqing Dang, Shengyu Wei, Yuning Du, et al · 2022
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Rethinking general underwater object detection: Datasets, challenges, and solutions
Chenping Fu, Risheng Liu, Xin Fan, Puyang Chen, Hao Fu, Wanqi Yuan, Ming Zhu, and Zhongxuan Luo · 2023
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Visual attention network
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A survey on vision transformer
Kai Han, Yunhe Wang, Hanting Chen, Xinghao Chen, Jianyuan Guo, Zhenhua Liu, Yehui Tang, An Xiao, Chunjing Xu, Yixing Xu, Zhaohui Yang, Yiman Zhang, and Dacheng Tao · 2023
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Large selective kernel network for remote sensing object detection
Yuxuan Li, Qibin Hou, Zhaohui Zheng, Ming-Ming Cheng, Jian Yang, and Xiang Li · 2023
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Edgenext: efficiently amalgamated cnn-transformer architecture for mobile vision applications
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Gold-yolo: Efficient object detector via gather-and-distribute mechanism
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Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
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DINO: DETR with improved denoising anchor boxes for end-to-end object detection
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Conv2former: A simple transformer-style convnet for visual recognition
Qibin Hou, Cheng-Ze Lu, Ming-Ming Cheng, and Jiashi Feng · 2024
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Towards raw object detection in diverse conditions, 2024
Zhong-Yu Li, Xin Jin, Boyuan Sun, Chun-Le Guo, and Ming-Ming Cheng · 2024
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Yolov10: Real-time end-to-end object detection
Ao Wang, Hui Chen, Lihao Liu, Kai Chen, Zijia Lin, Jungong Han, and Guiguang Ding · 2024
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Yolov9: Learning what you want to learn using programmable gradient information
Chien-Yao Wang, I-Hau Yeh, and Hong-Yuan Mark Liao · 2024
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Camoformer: Masked separable attention for camouflaged object detection
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Detrs beat yolos on real-time object detection
Yian Zhao, Wenyu Lv, Shangliang Xu, Jinman Wei, Guanzhong Wang, Qingqing Dang, Yi Liu, and Jie Chen · 2024
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Referring camouflaged object detection
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