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We present a novel framework to bootstrap Motion forecasting with Self-consistent Constraints (MISC).
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Vehicle trajectory prediction based on motion model and maneuver recognition
Adam Houenou, Philippe Bonnifait, Véronique Cherfaoui, and Wen Yao · 2013
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Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks
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The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains
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Philip Bachman, Ouais Alsharif, and Doina Precup · 2014
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Making bertha drive—an autonomous journey on a historic route
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Convolutional networks on graphs for learning molecular fingerprints
David K Duvenaud, Dougal Maclaurin, Jorge Iparraguirre, Rafael Bombarell, Timothy Hirzel, Alán Aspuru-Guzik, and Ryan P Adams · 2015
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Deep convolutional networks on graph-structured data
Mikael Henaff, Joan Bruna, and Yann LeCun · 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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Temporal ensembling for semi-supervised learning
Samuli Laine and Timo Aila · 2016
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Stochastic multiple choice learning for training diverse deep ensembles
Stefan Lee, Senthil Purushwalkam Shiva Prakash, Michael Cogswell, Viresh Ranjan, David Crandall, and Dhruv Batra · 2016
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Regularization with stochastic transformations and perturbations for deep semi-supervised learning
Mehdi Sajjadi, Mehran Javanmardi, and Tolga Tasdizen · 2016
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Learning in an uncertain world: Representing ambiguity through multiple hypotheses
Christian Rupprecht, Iro Laina, Robert DiPietro, Maximilian Baust, Federico Tombari, Nassir Navab, and Gregory D Hager · 2017
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Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen and Harri Valpola · 2017
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Vehicle trajectory prediction by integrating physics-and maneuver-based approaches using interactive multiple models
Guotao Xie, Hongbo Gao, Lijun Qian, Bin Huang, Keqiang Li, and Jianqiang Wang · 2017
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Unsupervised learning of depth and ego-motion from video
Tinghui Zhou, Matthew Brown, Noah Snavely, and David G Lowe · 2017
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Cascade r-cnn: Delving into high quality object detection
Zhaowei Cai and Nuno Vasconcelos · 2018
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Intentnet: Learning to predict intention from raw sensor data
Sergio Casas, Wenjie Luo, and Raquel Urtasun · 2018
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Baidu apollo em motion planner
Haoyang Fan, Fan Zhu, Changchun Liu, Liangliang Zhang, Li Zhuang, Dong Li, Weicheng Zhu, Jiangtao Hu, Hongye Li, and Qi Kong · 2018
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Interaction-aware probabilistic behavior prediction in urban environments
Jens Schulz, Constantin Hubmann, Julian Löchner, and Darius Burschka · 2018
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Chauffeurnet
Mayank Bansal, Alex Krizhevsky, and Abhijit Ogale · 2019
Quo vadis? meaningful multiple trajectory hypotheses prediction in autonomous driving
Antonia Breuer, Quy Le Xuan, Jan-Aike Termöhlen, Silviu Homoceanu, and Tim Fingscheidt · 2021
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Large scale interactive motion forecasting for autonomous driving: The waymo open motion dataset
Scott Ettinger, Shuyang Cheng, Benjamin Caine, Chenxi Liu, Hang Zhao, Sabeek Pradhan, Yuning Chai, Ben Sapp, Charles R Qi, Yin Zhou, et al · 2021
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Home: Heatmap output for future motion estimation
Thomas Gilles, Stefano Sabatini, Dzmitry Tsishkou, Bogdan Stanciulescu, and Fabien Moutarde · 2021
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Densetnt: End-to-end trajectory prediction from dense goal sets
Junru Gu, Chen Sun, and Hang Zhao · 2021
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Multimodal motion prediction with stacked transformers
Yicheng Liu, Jinghuai Zhang, Liangji Fang, Qinhong Jiang, and Bolei Zhou · 2021
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Multipath: Multiple probabilistic anchor trajectory hypotheses for behavior prediction
Yuning Chai, Benjamin Sapp, Mayank Bansal, and Dragomir Anguelov · 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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Overcoming limitations of mixture density networks: A sampling and fitting framework for multimodal future prediction
Osama Makansi, Eddy Ilg, Ozgun Cicek, and Thomas Brox · 2019
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A hierarchical network for diverse trajectory proposals
NN Sriram, Gourav Kumar, Abhay Singh, M Siva Karthik, Saket Saurav, Brojeshwar Bhowrnick, and K Madhava Krishna · 2019
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Learning correspondence from the cycle-consistency of time
Xiaolong Wang, Allan Jabri, and Alexei A Efros · 2019
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End-to-end interpretable neural motion planner
Wenyuan Zeng, Wenjie Luo, Simon Suo, Abbas Sadat, Bin Yang, Sergio Casas, and Raquel Urtasun · 2019
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Divide-and-conquer for lane-aware diverse trajectory prediction
Sriram Narayanan, Ramin Moslemi, Francesco Pittaluga, Buyu Liu, and Manmohan Chandraker · 2021
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Scene transformer: A unified multi-task model for behavior prediction and planning
Jiquan Ngiam, Benjamin Caine, Vijay Vasudevan, Zhengdong Zhang, Hao-Tien Lewis Chiang, Jeffrey Ling, Rebecca Roelofs, Alex Bewley, Chenxi Liu, Ashish Venugopal, et al · 2021
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Internal video inpainting by implicit long-range propagation
Hao Ouyang, Tengfei Wang, and Qifeng Chen · 2021
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Learning to predict vehicle trajectories with model-based planning
Haoran Song, Di Luan, Wenchao Ding, Michael Y Wang, and Qifeng Chen · 2021
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Multipath++: Efficient information fusion and trajectory aggregation for behavior prediction
Balakrishnan Varadarajan, Ahmed Hefny, Avikalp Srivastava, Khaled S Refaat, Nigamaa Nayakanti, Andre Cornman, Kan Chen, Bertrand Douillard, Chi Pang Lam, Dragomir Anguelov, et al · 2021
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Dual-camera super-resolution with aligned attention modules
Tengfei Wang, Jiaxin Xie, Wenxiu Sun, Qiong Yan, and Qifeng Chen · 2021
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Tpcn: Temporal point cloud networks for motion forecasting
Maosheng Ye, Tongyi Cao, and Qifeng Chen · 2021
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Lanercnn: Distributed representations for graph-centric motion forecasting
Wenyuan Zeng, Ming Liang, Renjie Liao, and Raquel Urtasun · 2021
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Se-ssd: Self-ensembling single-stage object detector from point cloud
Wu Zheng, Weiliang Tang, Li Jiang, and Chi-Wing Fu · 2021
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Ssl-lanes: Self-supervised learning for motion forecasting in autonomous driving
Prarthana Bhattacharyya, Chengjie Huang, and Krzysztof Czarnecki · 2022
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Improving motion forecasting for autonomous driving with the cycle consistency loss
Titas Chakraborty, Akshay Bhagat, and Henggang Cui · 2022
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Gohome: Graph-oriented heatmap output for future motion estimation
Thomas Gilles, Stefano Sabatini, Dzmitry Tsishkou, Bogdan Stanciulescu, and Fabien Moutarde · 2022
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Kemp: Keyframe-based hierarchical end-to-end deep model for long-term trajectory prediction
Qiujing Lu, Weiqiao Han, Jeffrey Ling, Minfa Wang, Haoyu Chen, Balakrishnan Varadarajan, and Paul Covington · 2022
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Narrowing the coordinate-frame gap in behavior prediction models: Distillation for efficient and accurate scene-centric motion forecasting
DiJia Andy Su, Bertrand Douillard, Rami Al-Rfou, Cheol Park, and Benjamin Sapp · 2022
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Hivt: Hierarchical vector transformer for multi-agent motion prediction
Zikang Zhou, Luyao Ye, Jianping Wang, Kui Wu, and Kejie Lu · 2022
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