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3D object detection networks tend to be biased towards the data they are trained on.
The self-organizing map
Teuvo Kohonen · 1998
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Are we ready for autonomous driving? the kitti vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
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A new active labeling method for deep learning
Dan Wang and Yi Shang · 2014
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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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Gaussian error linear units (gelus)
Dan Hendrycks and Kevin Gimpel · 2016
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Multi-view 3d object detection network for autonomous driving
Xiaozhi Chen, Huimin Ma, Ji Wan, Bo Li, and Tian Xia · 2017
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Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 2017
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Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Charles R Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Learning class prototypes via structure alignment for zero-shot recognition
Huajie Jiang, Ruiping Wang, Shiguang Shan, and Xilin Chen · 2018
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Joint 3d proposal generation and object detection from view aggregation
Jason Ku, Melissa Mozifian, Jungwook Lee, Ali Harakeh, and Steven L Waslander · 2018
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Second: Sparsely embedded convolutional detection
Yan Yan, Yuxing Mao, and Bo Li · 2018
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Robust classification with convolutional prototype learning
Hong-Ming Yang, Xu-Yao Zhang, Fei Yin, and Cheng-Lin Liu · 2018
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Ipod: Intensive point-based object detector for point cloud
Zetong Yang, Yanan Sun, Shu Liu, Xiaoyong Shen, and Jiaya Jia · 2018
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Voxelnet: End-to-end learning for point cloud based 3d object detection
Yin Zhou and Oncel Tuzel · 2018
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Exploring object relation in mean teacher for cross-domain detection
Qi Cai, Yingwei Pan, C. Ngo, Xinmei Tian, Ling yu Duan, and Ting Yao · 2019
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Argoverse: 3d tracking and forecasting with rich maps
Ming-Fang Chang, John Lambert, Patsorn Sangkloy, Jagjeet Singh, Slawomir Bak, Andrew Hartnett, De Wang, Peter Carr, Simon Lucey, Deva Ramanan, et al · 2019
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A robust learning approach to domain adaptive object detection
Mehran Khodabandeh, Arash Vahdat, Mani Ranjbar, and William G. Macready · 2019
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Pointpillars: Fast encoders for object detection from point clouds
Alex H Lang, Sourabh Vora, Holger Caesar, Lubing Zhou, Jiong Yang, and Oscar Beijbom · 2019
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Automatic adaptation of object detectors to new domains using self-training
Aruni RoyChowdhury, Prithvijit Chakrabarty, Ashish Singh, SouYoung Jin, Huaizu Jiang, Liangliang Cao, and Erik G. Learned-Miller · 2019
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Pointrcnn: 3d object proposal generation and detection from point cloud
Shaoshuai Shi, Xiaogang Wang, and Hongsheng Li · 2019
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Train in germany, test in the usa: Making 3d object detectors generalize
Yan Wang, X. Chen, Yurong You, Li Erran, Bharath Hariharan, M. Campbell, Kilian Q. Weinberger, and Wei-Lun Chao · 2020
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Self-training with noisy student improves imagenet classification
Qizhe Xie, Minh-Thang Luong, Eduard Hovy, and Quoc V Le · 2020
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3dssd: Point-based 3d single stage object detector
Zetong Yang, Yanan Sun, Shu Liu, and Jiaya Jia · 2020
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Pseudo-labeling for scalable 3d object detection
Benjamin Caine, R. Roelofs, Vijay Vasudevan, Jiquan Ngiam, Yuning Chai, Z. Chen, and Jonathon Shlens · 2021
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Pseudo-labeling for scalable 3d object detection
Benjamin Caine, Rebecca Roelofs, Vijay Vasudevan, Jiquan Ngiam, Yuning Chai, Z. Chen, and Jonathon Shlens · 2021
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Shaoshuai Shi, Zhe Wang, X. Wang, and Hongsheng Li · 2019
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Mvx-net: Multimodal voxelnet for 3d object detection
Vishwanath Sindagi, Yin Zhou, and Oncel Tuzel · 2019
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Confidence regularized self-training
Yang Zou, Zhiding Yu, Xiaofeng Liu, BVK Kumar, and Jinsong Wang · 2019
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nuscenes: A multimodal dataset for autonomous driving
Holger Caesar, Varun Bankiti, Alex H. Lang, Sourabh Vora, Venice Erin Liong, Q. Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom · 2020
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One thousand and one hours: Self-driving motion prediction dataset
John Houston, Guido Zuidhof, Luca Bergamini, Yawei Ye, Long Chen, Ashesh Jain, Sammy Omari, Vladimir Iglovikov, and Peter Ondruska · 2020
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Universal source-free domain adaptation
Jogendra Nath Kundu, Naveen Venkat, V. RahulM., and R. Venkatesh Babu · 2020
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Sf-uda3d: Source-free unsupervised domain adaptation for lidar-based 3d object detection
Cristiano Saltori, St’ephane Lathuili’ere, N. Sebe, E. Ricci, and Fabio Galasso · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, and Neil Houlsby · 2021
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A free lunch for unsupervised domain adaptive object detection without source data
Xianfeng Li, Weijie Chen, Di Xie, Shicai Yang, Peng Yuan, Shiliang Pu, and Yueting Zhuang · 2021
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Unsupervised domain adaptive 3d detection with multi-level consistency
Zhipeng Luo, Zhongang Cai, Changqing Zhou, Gong-Duo Zhang, Haiyu Zhao, Shuai Yi, Shijian Lu, Hongsheng Li, Shanghang Zhang, and Ziwei Liu · 2021
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Unsupervised domain adaptation of object detectors: A survey, 2021
Poojan Oza, Vishwanath A. Sindagi, Vibashan VS, and Vishal M. Patel · 2021
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Canadian adverse driving conditions dataset
Matthew Pitropov, Danson Evan Garcia, Jason Rebello, Michael Smart, Carlos Wang, Krzysztof Czarnecki, and Steven Waslander · 2021
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Active domain adaptation via clustering uncertainty-weighted embeddings
Viraj Prabhu, Arjun Chandrasekaran, Kate Saenko, and Judy Hoffman · 2021
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Grid-gcn for fast and scalable point cloud learning
Qiangeng Xu, Yin Zhou, Weiyue Wang, Charles R. Qi, and Dragomir Anguelov · 2021
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St3d: Self-training for unsupervised domain adaptation on 3d object detection
Jihan Yang, Shaoshuai Shi, Zhe Wang, Hongsheng Li, and Xiaojuan Qi · 2021
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Generalized source-free domain adaptation
Shiqi Yang, Yaxing Wang, Joost van de Weijer, Luis Herranz, and Shangling Jui · 2021
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Prototypical pseudo label denoising and target structure learning for domain adaptive semantic segmentation
Pan Zhang, Bo Zhang, Ting Zhang, Dong Chen, Yong Wang, and Fang Wen · 2021
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