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Knowledge distillation(KD) is a widely-used technique to train compact models in object detection.
Pearson correlation coefficient
Jacob Benesty, Jingdong Chen, Yiteng Huang, and Israel Cohen · 2009
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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Fitnets: Hints for thin deep nets
Adriana Romero, Nicolas Ballas, Samira Ebrahimi Kahou, Antoine Chassang, Carlo Gatta, and Yoshua Bengio · 2014
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, Jeff Dean, et al · 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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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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Instance normalization: The missing ingredient for fast stylization
Dmitry Ulyanov, Andrea Vedaldi, and Victor Lempitsky · 2016
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Learning efficient object detection models with knowledge distillation
Guobin Chen, Wongun Choi, Xiang Yu, Tony Han, and Manmohan Chandraker · 2017
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Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
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Like what you like: Knowledge distill via neuron selectivity transfer
Zehao Huang and Naiyan Wang · 2017
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Mimicking very efficient network for object detection
Quanquan Li, Shengying Jin, and Junjie Yan · 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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Automatic differentiation in pytorch
Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer · 2017
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A gift from knowledge distillation: Fast optimization, network minimization and transfer learning
Junho Yim, Donggyu Joo, Jihoon Bae, and Junmo Kim · 2017
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Cascade r-cnn: Delving into high quality object detection
Zhaowei Cai and Nuno Vasconcelos · 2018
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Yolov3: An incremental improvement
Joseph Redmon and Ali Farhadi · 2018
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Group normalization
Yuxin Wu and Kaiming He · 2018
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Variational information distillation for knowledge transfer
Sungsoo Ahn, Shell Xu Hu, Andreas Damianou, Neil D Lawrence, and Zhenwen Dai · 2019
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Cascade r-cnn: high quality object detection and instance segmentation
Zhaowei Cai and Nuno Vasconcelos · 2019
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Gcnet: Non-local networks meet squeeze-excitation networks and beyond
Yue Cao, Jiarui Xu, Stephen Lin, Fangyun Wei, and Han Hu · 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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Distilling object detectors with task adaptive regularization
Ruoyu Sun, Fuhui Tang, Xiaopeng Zhang, Hongkai Xiong, and Qi Tian · 2020
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Intra-class feature variation distillation for semantic segmentation
Yukang Wang, Wei Zhou, Tao Jiang, Xiang Bai, and Yongchao Xu · 2020
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Improve object detection with feature-based knowledge distillation: Towards accurate and efficient detectors
Linfeng Zhang and Kaisheng Ma · 2020
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Openmmlab model compression toolbox and benchmark
MMRazor Contributors · 2021
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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, et al · 2019
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Centernet: Keypoint triplets for object detection
Kaiwen Duan, Song Bai, Lingxi Xie, Honggang Qi, Qingming Huang, and Qi Tian · 2019
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Knowledge transfer via distillation of activation boundaries formed by hidden neurons
Byeongho Heo, Minsik Lee, Sangdoo Yun, and Jin Young Choi · 2019
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Knowledge distillation via instance relationship graph
Yufan Liu, Jiajiong Cao, Bing Li, Chunfeng Yuan, Weiming Hu, Yangxi Li, and Yunqiang Duan · 2019
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Relational knowledge distillation
Wonpyo Park, Dongju Kim, Yan Lu, and Minsu Cho · 2019
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Contrastive representation distillation
Yonglong Tian, Dilip Krishnan, and Phillip Isola · 2019
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General instance distillation for object detection
Xing Dai, Zeren Jiang, Zhao Wu, Yiping Bao, Zhicheng Wang, Si Liu, and Erjin Zhou · 2021
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Tood: Task-aligned one-stage object detection
Chengjian Feng, Yujie Zhong, Yu Gao, Matthew R Scott, and Weilin Huang · 2021
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Distilling object detectors via decoupled features
Jianyuan Guo, Kai Han, Yunhe Wang, Han Wu, Xinghao Chen, Chunjing Xu, and Chang Xu · 2021
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Instance-conditional knowledge distillation for object detection
Zijian Kang, Peizhen Zhang, Xiangyu Zhang, Jian Sun, and Nanning Zheng · 2021
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Gang Li, Xiang Li, Yujie Wang, Shanshan Zhang, Yichao Wu, and Ding Liang · 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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Channel-wise knowledge distillation for dense prediction
Changyong Shu, Yifan Liu, Jianfei Gao, Zheng Yan, and Chunhua Shen · 2021
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Focal and global knowledge distillation for detectors
Zhendong Yang, Zhe Li, Xiaohu Jiang, Yuan Gong, Zehuan Yuan, Danpei Zhao, and Chun Yuan · 2021
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G-detkd: Towards general distillation framework for object detectors via contrastive and semantic-guided feature imitation
Lewei Yao, Renjie Pi, Hang Xu, Wei Zhang, Zhenguo Li, and Tong Zhang · 2021
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Distilling object detectors with feature richness
Du Zhixing, Rui Zhang, Ming Chang, Shaoli Liu, Tianshi Chen, Yunji Chen, et al · 2021
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Decoupled knowledge distillation
Borui Zhao, Quan Cui, Renjie Song, Yiyu Qiu, and Jiajun Liang · 2022
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