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Model efficiency has become increasingly important in computer vision.
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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Overfeat: Integrated recognition, localization and detection using convolutional networks
Pierre Sermanet, David Eigen, Xiang Zhang, Michaël Mathieu, Rob Fergus, and Yann LeCun · 2014
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Rigid-motion scattering for image classification
Laurent Sifre · 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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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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A unified multi-scale deep convolutional neural network for fast object detection
Zhaowei Cai, Quanfu Fan, Rogerio S Feris, and Nuno Vasconcelos · 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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Gaussian error linear units (gelus)
Dan Hendrycks and Kevin Gimpel · 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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Gated feedback refinement network for dense image labeling
Md Amirul Islam, Mrigank Rochan, Neil DB Bruce, and Yang Wang · 2017
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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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Xception: Deep learning with depthwise separable convolutions
François Chollet · 2017
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Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 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, et al · 2017
Earlier work this paper cites.
Feature pyramid networks for object detection
Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie · 2017
Cited alongside, same era.
Focal loss for dense object detection
Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie · 2017
Cited alongside, same era.
Yolo9000: better, faster, stronger
Joseph Redmon and Ali Farhadi · 2017
Cited alongside, same era.
Aggregated residual transformations for deep neural networks
Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, and Kaiming He · 2017
Cited alongside, same era.
Cascade r-cnn: Delving into high quality object detection
Zhaowei Cai and Nuno Vasconcelos · 2018
Cited alongside, same era.
Encoder-decoder with atrous separable convolution for semantic image segmentation
Liang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroff, and Hartwig Adam · 2018
Yolov3: An incremental improvement
Joseph Redmon and Ali Farhadi · 2018
Later among the works it cites.
Scale-transferrable object detection
Peng Zhou, Bingbing Ni, Cong Geng, Jianguo Hu, and Yi Xu · 2018
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Nas-fpn: Learning scalable feature pyramid architecture for object detection
Golnaz Ghiasi, Tsung-Yi Lin, Ruoming Pang, and Quoc V. Le · 2019
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Rethinking imagenet pre-training
Kaiming He, Ross Girshick, and Piotr Dollár · 2019
Closest in time.
Searching for mobilenetv3
Andrew Howard, Mark Sandler, Grace Chu, Liang-Chieh Chen, Bo Chen, Mingxing Tan, Weijun Wang, Yukun Zhu, Ruoming Pang, Vijay Vasudevan, Quoc V. Le, and Hartwig Adam · 2019
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Panoptic feature pyramid networks
Alexander Kirillov, Ross Girshick, Kaiming He, and Piotr Dollár · 2019
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Cited alongside, same era.
Sigmoid-weighted linear units for neural network function approximation in reinforcement learning
Stefan Elfwing, Eiji Uchibe, and Kenji Doya · 2018
Cited alongside, same era.
Parallel feature pyramid network for object detection
Seung-Wook Kim, Hyong-Keun Kook, Jee-Young Sun, Mun-Cheon Kang, and Sung-Jea Ko · 2018
Cited alongside, same era.
Deep feature pyramid reconfiguration for object detection
Tao Kong, Fuchun Sun, Chuanqi Tan, Huaping Liu, and Wenbing Huang · 2018
Cited alongside, same era.
Cornernet: Detecting objects as paired keypoints
Hei Law and Jia Deng · 2018
Cited alongside, same era.
Pyramid attention networks
Hanchao Li, Pengfei Xiong, Jie An, and Lingxue Wang · 2018
Cited alongside, same era.
Path aggregation network for instance segmentation
Shu Liu, Lu Qi, Haifang Qin, Jianping Shi, and Jiaya Jia · 2018
Cited alongside, same era.
Closest in time.
Rethinking the value of network pruning
Zhuang Liu, Mingjie Sun, Tinghui Zhou, Gao Huang, and Trevor Darrell · 2019
Closest in time.
Regularized evolution for image classifier architecture search
Esteban Real, Alok Aggarwal, Yanping Huang, and Quoc V Le · 2019
Closest in time.
Mnasnet: Platform-aware neural architecture search for mobile
Mingxing Tan, Bo Chen, Ruoming Pang, Vijay Vasudevan, and Quoc V Le · 2019
Closest in time.
Efficientnet: Rethinking model scaling for convolutional neural networks
Mingxing Tan and Quoc V. Le · 2019
Closest in time.
Fcos: Fully convolutional one-stage object detection
Zhi Tian, Chunhua Shen, Hao Chen, and Tong He · 2019
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M2det: A single-shot object detector based on multi-level feature pyramid network
Qijie Zhao, Tao Sheng, Yongtao Wang, Zhi Tang, Ying Chen, Ling Cai, and Haibin Ling · 2019
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Xingyi Zhou, Dequan Wang, and Philipp Krähenbühl · 2019
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Learning data augmentation strategies for object detection
Barret Zoph, Ekin D. Cubuk, Golnaz Ghiasi, Tsung-Yi Lin, Jonathon Shlens, and Quoc V. Le · 2019
Closest in time.
https://github.com/facebookresearch/detectron2
Detectron2 · 2020
Closest in time.