Fetching the paper…
Reading the bibliography…
Building reliable object detectors that are robust to domain shifts, such as various changes in context, viewpoint, and object appearances, is critical for real-world applications.
Information theory and statistical mechanics
Edwin T Jaynes · 1957
Earlier work this paper cites.
Information theory and statistical mechanics. ii
Edwin T Jaynes · 1957
Earlier work this paper cites.
Linearly-solvable markov decision problems
Emanuel Todorov et al · 2006
Earlier work this paper cites.
Extracting and composing robust features with denoising autoencoders
Pascal Vincent, Hugo Larochelle, Yoshua Bengio, and Pierre-Antoine Manzagol · 2008
Earlier work this paper cites.
Modeling purposeful adaptive behavior with the principle of maximum causal entropy
Brian D Ziebart · 2010
Earlier work this paper cites.
On stochastic optimal control and reinforcement learning by approximate inference
Konrad Rawlik, Marc Toussaint, and Sethu Vijayakumar · 2012
Earlier work this paper cites.
Unsupervised visual representation learning by context prediction
Carl Doersch, Abhinav Gupta, and Alexei A Efros · 2015
Earlier work this paper cites.
Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
Earlier work this paper cites.
Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2015
Earlier work this paper cites.
Unsupervised learning of visual representations using videos
Xiaolong Wang and Abhinav Gupta · 2015
Earlier work this paper cites.
The cityscapes dataset for semantic urban scene understanding
Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, and Bernt Schiele · 2016
Earlier work this paper cites.
Autonomous driving in the real world: Experiences with tesla autopilot and summon
Murat Dikmen and Catherine M Burns · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Unsupervised learning of visual representations by solving jigsaw puzzles
Mehdi Noroozi and Paolo Favaro · 2016
Earlier work this paper cites.
Ambient sound provides supervision for visual learning
Andrew Owens, Jiajun Wu, Josh H McDermott, William T Freeman, and Antonio Torralba · 2016
Earlier work this paper cites.
Context encoders: Feature learning by inpainting
Deepak Pathak, Philipp Krahenbuhl, Jeff Donahue, Trevor Darrell, and Alexei A Efros · 2016
Earlier work this paper cites.
Driving in the matrix: Can virtual worlds replace human-generated annotations for real world tasks?
Matthew Johnson-Roberson, Charles Barto, Rounak Mehta, Sharath Nittur Sridhar, Karl Rosaen, and Ram Vasudevan · 2017
Earlier work this paper cites.
Autonomous vehicle safety: An interdisciplinary challenge
Philip Koopman and Michael Wagner · 2017
Earlier work this paper cites.
Feature pyramid networks for object detection
Tsung-Yi Lin, Piotr Dollar, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie · 2017
Cited alongside, same era.
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.
Split-brain autoencoders: Unsupervised learning by cross-channel prediction
Richard Zhang, Phillip Isola, and Alexei A Efros · 2017
Cited alongside, same era.
Domain adaptive faster r-cnn for object detection in the wild
Yuhua Chen, Wen Li, Christos Sakaridis, Dengxin Dai, and Luc Van Gool · 2018
Cited alongside, same era.
Unsupervised representation learning by predicting image rotations
Spyros Gidaris, Praveer Singh, and Nikos Komodakis · 2018
Cited alongside, same era.
Benchmarking neural network robustness to common corruptions and perturbations
Dan Hendrycks and Thomas Dietterich · 2018
Strong-weak distribution alignment for adaptive object detection
Kuniaki Saito, Yoshitaka Ushiku, Tatsuya Harada, and Kate Saenko · 2019
Later among the works it cites.
A systematic framework for natural perturbations from videos
Vaishaal Shankar, Achal Dave, Rebecca Roelofs, Deva Ramanan, Benjamin Recht, and Ludwig Schmidt · 2019
Later among the works it cites.
Unsupervised domain adaptation through self-supervision
Yu Sun, Eric Tzeng, Trevor Darrell, and Alexei A Efros · 2019
Later among the works it cites.
Learning correspondence from the cycle-consistency of time
Xiaolong Wang, Allan Jabri, and Alexei A Efros · 2019
Later among the works it cites.
Detectron2
Yuxin Wu, Alexander Kirillov, Francisco Massa, Wan-Yen Lo, and Ross Girshick · 2019
Later among the works it cites.
Adapting object detectors via selective cross-domain alignment
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Do cifar-10 classifiers generalize to cifar-10?
Benjamin Recht, Rebecca Roelofs, Ludwig Schmidt, and Vaishaal Shankar · 2018
Cited alongside, same era.
Semantic foggy scene understanding with synthetic data
Christos Sakaridis, Dengxin Dai, and Luc Van Gool · 2018
Cited alongside, same era.
Time-contrastive networks: Self-supervised learning from video
Pierre Sermanet, Corey Lynch, Yevgen Chebotar, Jasmine Hsu, Eric Jang, Stefan Schaal, Sergey Levine, and Google Brain · 2018
Cited alongside, same era.
Exploring object relation in mean teacher for cross-domain detection
Qi Cai, Yingwei Pan, Chong-Wah Ngo, Xinmei Tian, Lingyu Duan, and Ting Yao · 2019
Cited alongside, same era.
Temporal cycle-consistency learning
Debidatta Dwibedi, Yusuf Aytar, Jonathan Tompson, Pierre Sermanet, and Andrew Zisserman · 2019
Cited alongside, same era.
Imagenet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
Robert Geirhos, Patricia Rubisch, Claudio Michaelis, Matthias Bethge, Felix A. Wichmann, and Wieland Brendel · 2019
Cited alongside, same era.
Xinge Zhu, Jiangmiao Pang, Ceyuan Yang, Jianping Shi, and Dahua Lin · 2019
Later among the works it cites.
End-to-end object detection with transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
Later among the works it cites.
AugMix: A simple data processing method to improve robustness and uncertainty
Dan Hendrycks, Norman Mu, Ekin D. Cubuk, Barret Zoph, Justin Gilmer, and Balaji Lakshminarayanan · 2020
Later among the works it cites.
Every pixel matters: Center-aware feature alignment for domain adaptive object detector
Cheng-Chun Hsu, Yi-Hsuan Tsai, Yen-Yu Lin, and Ming-Hsuan Yang · 2020
Later among the works it cites.
Adapting object detectors with conditional domain normalization
Peng Su, Kun Wang, Xingyu Zeng, Shixiang Tang, Dapeng Chen, Di Qiu, and Xiaogang Wang · 2020
Later among the works it cites.
Scalability in perception for autonomous driving: Waymo open dataset
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, et al · 2020
Later among the works it cites.
Exploring categorical regularization for domain adaptive object detection
Chang-Dong Xu, Xing-Ran Zhao, Xin Jin, and Xiu-Shen Wei · 2020
Later among the works it cites.
Cross-domain detection via graph-induced prototype alignment
Minghao Xu, Hang Wang, Bingbing Ni, Qi Tian, and Wenjun Zhang · 2020
Later among the works it cites.
Bdd100k: A diverse driving dataset for heterogeneous multitask learning
Fisher Yu, Haofeng Chen, Xin Wang, Wenqi Xian, Yingying Chen, Fangchen Liu, Vashisht Madhavan, and Trevor Darrell · 2020
Later among the works it cites.
Collaborative training between region proposal localization and classi? cation for domain adaptive object detection
Ganlong Zhao, Guanbin Li, Ruijia Xu, and Liang Lin · 2020
Later among the works it cites.
Maximum entropy rl (provably) solves some robust rl problems, 2021
Benjamin Eysenbach and Sergey Levine · 2021
Closest in time.
WILDS: A benchmark of in-the-wild distribution shifts
Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Irena Gao, Tony Lee, Etienne David, Ian Stavness, Wei Guo, Berton A. Earnshaw, Imran S. Haque, Sara Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, and Percy Liang · 2021
Closest in time.