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A common practice in transfer learning is to initialize the downstream model weights by pre-training on a data-abundant upstream task.
Catastrophic forgetting in connectionist networks
Robert M. French · 1999
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Semi-supervised self-training of object detection models
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A survey on transfer learning
Sinno Jialin Pan and Qiang Yang · 2009
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The arcade learning environment: An evaluation platform for general agents
Marc G Bellemare, Yavar Naddaf, Joel Veness, and Michael Bowling · 2013
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Microsoft coco: Common objects in context, 2014
Tsung-Yi Lin, Michael Maire, Serge Belongie, Lubomir Bourdev, Ross Girshick, James Hays, Pietro Perona, Deva Ramanan, C. Lawrence Zitnick, and Piotr Dollár · 2014
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2015
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Distilling the knowledge in a neural network
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Towards computational baby learning: A weakly-supervised approach for object detection
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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 Bernstein, et al · 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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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 · 2016
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Xception: Deep learning with depthwise separable convolutions
François Chollet · 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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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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Extreme clicking for efficient object annotation
Dim P. Papadopoulos, Jasper R. R. Uijlings, Frank Keller, and Vittorio Ferrari · 2017
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Learning multiple visual domains with residual adapters
Sylvestre-Alvise Rebuffi, Hakan Bilen, and Andrea Vedaldi · 2017
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Revisiting unreasonable effectiveness of data in deep learning era
Chen Sun, Abhinav Shrivastava, Saurabh Singh, and Abhinav Gupta · 2017
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Cascade r-cnn: Delving into high quality object detection
Zhaowei Cai and Nuno Vasconcelos · 2018
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Feature-wise transformations
Vincent Dumoulin, Ethan Perez, Nathan Schucher, Florian Strub, Harm de Vries, Aaron Courville, and Yoshua Bengio · 2018
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Exploring the limits of weakly supervised pretraining
Dhruv Mahajan, Ross Girshick, Vignesh Ramanathan, Kaiming He, Manohar Paluri, Yixuan Li, Ashwin Bharambe, and Laurens Van Der Maaten · 2018
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Exploring the limits of weakly supervised pretraining
Dhruv Mahajan, Ross Girshick, Vignesh Ramanathan, Kaiming He, Manohar Paluri, Yixuan Li, Ashwin Bharambe, and Laurens van der Maaten · 2018
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Efficient parametrization of multi-domain deep neural networks
Efficientdet: Scalable and efficient object detection
Mingxing Tan, Ruoming Pang, and Quoc V. Le · 2020
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Rethinking pre-training and self-training
Barret Zoph, Golnaz Ghiasi, Tsung-Yi Lin, Yin Cui, Hanxiao Liu, Ekin D Cubuk, and Quoc V Le · 2020
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Detreg: Unsupervised pretraining with region priors for object detection, 2021
Amir Bar, Xin Wang, Vadim Kantorov, Colorado J Reed, Roei Herzig, Gal Chechik, Anna Rohrbach, Trevor Darrell, and Amir Globerson · 2021
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Revisiting rainbow: Promoting more insightful and inclusive deep reinforcement learning research
Johan Samir Obando Ceron and Pablo Samuel Castro · 2021
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Up-detr: Unsupervised pre-training for object detection with transformers
Zhigang Dai, Bolun Cai, Yugeng Lin, and Junying Chen · 2021
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Simple training strategies and model scaling for object detection
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Sylvestre-Alvise Rebuffi, Hakan Bilen, and Andrea Vedaldi · 2018
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LVIS: A dataset for large vocabulary instance segmentation
Agrim Gupta, Piotr Dollár, and Ross B. Girshick · 2019
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Rethinking imagenet pre-training
Kaiming He, Ross Girshick, and Piotr Dollár · 2019
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Parameter-efficient transfer learning for NLP
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin de Laroussilhe, Andrea Gesmundo, Mona Attariyan, and Sylvain Gelly · 2019
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Consistency-based semi-supervised learning for object detection
Jisoo Jeong, Seungeui Lee, Jeesoo Kim, and Nojun Kwak · 2019
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Do better imagenet models transfer better?
Simon Kornblith, Jonathon Shlens, and Quoc V. Le · 2019
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Scaling object detection by transferring classification weights
Jason Kuen, Federico Perazzi, Zhe Lin, Jianming Zhang, and Yap-Peng Tan · 2019
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Xianzhi Du, Barret Zoph, Wei-Chih Hung, and Tsung-Yi Lin · 2021
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Simple training strategies and model scaling for object detection, 2021
Xianzhi Du, Barret Zoph, Wei-Chih Hung, and Tsung-Yi Lin · 2021
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Simple training strategies and model scaling for object detection
Xianzhi Du, Barret Zoph, Wei-Chih Hung, and Tsung-Yi Lin · 2021
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Improving task adaptation for cross-domain few-shot learning
Wei-Hong Li, Xialei Liu, and Hakan Bilen · 2021
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Rethinking training from scratch for object detection, 2021
Yang Li, Hong Zhang, and Yu Zhang · 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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Compacter: Efficient low-rank hypercomplex adapter layers
Rabeeh Karimi Mahabadi, James Henderson, and Sebastian Ruder · 2021
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Adapterfusion: Non-destructive task composition for transfer learning, 2021
Jonas Pfeiffer, Aishwarya Kamath, Andreas Rücklé, Kyunghyun Cho, and Iryna Gurevych · 2021
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Scalable transfer learning with expert models
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Predet: Large-scale weakly supervised pre-training for detection
Vignesh Ramanathan, Rui Wang, and Dhruv Mahajan · 2021
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Deep learning’s diminishing returns: The cost of improvement is becoming unsustainable
Neil C Thompson, Kristjan Greenewald, Keeheon Lee, and Gabriel F Manso · 2021
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End-to-end semi-supervised object detection with soft teacher
Mengde Xu, Zheng Zhang, Han Hu, Jianfeng Wang, Lijuan Wang, Fangyun Wei, Xiang Bai, and Zicheng Liu · 2021
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