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Modeling the evolutions of driving scenarios is important for the evaluation and decision-making of autonomous driving systems.
Neural networks: a comprehensive foundation
Simon Haykin · 1994
Earlier work this paper cites.
Congested traffic states in empirical observations and microscopic simulations
Martin Treiber, Ansgar Hennecke, and Dirk Helbing · 2000
Earlier work this paper cites.
Deep residual learning for image recognition, 2015
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
Earlier work this paper cites.
Carla: An open urban driving simulator
Alexey Dosovitskiy, German Ros, Felipe Codevilla, Antonio Lopez, and Vladlen Koltun · 2017
Earlier work this paper cites.
Streetgan: Towards road network synthesis with generative adversarial networks
Stefan Hartmann, Michael Weinmann, Raoul Wessel, and Reinhard Klein · 2017
Earlier work this paper cites.
Neural discrete representation learning
Aaron Van Den Oord, Oriol Vinyals, et al · 2017
Earlier work this paper cites.
Convolutional social pooling for vehicle trajectory prediction
Nachiket Deo and Mohan M Trivedi · 2018
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An environment for autonomous driving decision-making
Edouard Leurent · 2018
Earlier work this paper cites.
Deepdrive: a simulator that allows anyone with a pc to push the state-of-the-art in self-driving
Deepdrive Team · 2019
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Generating diverse high-fidelity images with vq-vae-2
Ali Razavi, Aaron Van den Oord, and Oriol Vinyals · 2019
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Language models are few-shot learners, 2020
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
Earlier work this paper cites.
End-to-end object detection with transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
Earlier work this paper cites.
Improving the generalization of end-to-end driving through procedural generation
Quanyi Li, Zhenghao Peng, Qihang Zhang, Chunxiao Liu, and Bolei Zhou · 2020
Earlier work this paper cites.
Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d
Jonah Philion and Sanja Fidler · 2020
Earlier work this paper cites.
Taming transformers for high-resolution image synthesis, 2021
Patrick Esser, Robin Rombach, and Björn Ommer · 2021
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Panoptic nuscenes: A large-scale benchmark for lidar panoptic segmentation and tracking
Whye Kit Fong, Rohit Mohan, Juana Valeria Hurtado, Lubing Zhou, Holger Caesar, Oscar Beijbom, and Abhinav Valada · 2021
Earlier work this paper cites.
Adversarial reinforcement learning for procedural content generation
Linus Gisslén, Andy Eakins, Camilo Gordillo, Joakim Bergdahl, and Konrad Tollmar · 2021
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Junru Gu, Chen Sun, and Hang Zhao · 2021
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Bevdet: High-performance multi-camera 3d object detection in bird-eye-view
Junjie Huang, Guan Huang, Zheng Zhu, Yun Ye, and Dalong Du · 2021
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Drivergym: Democratising reinforcement learning for autonomous driving
Parth Kothari, Christian Perone, Luca Bergamini, Alexandre Alahi, and Peter Ondruska · 2021
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Zero-shot text-to-image generation, 2021
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever · 2021
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Planning-oriented autonomous driving
Yihan Hu, Jiazhi Yang, Li Chen, Keyu Li, Chonghao Sima, Xizhou Zhu, Siqi Chai, Senyao Du, Tianwei Lin, Wenhai Wang, et al · 2023
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Vad: Vectorized scene representation for efficient autonomous driving
Bo Jiang, Shaoyu Chen, Qing Xu, Bencheng Liao, Jiajie Chen, Helong Zhou, Qian Zhang, Wenyu Liu, Chang Huang, and Xinggang Wang · 2023
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Vectormapnet: End-to-end vectorized hd map learning
Yicheng Liu, Tianyuan Yuan, Yue Wang, Yilun Wang, and Hang Zhao · 2023
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Motionlm: Multi-agent motion forecasting as language modeling
Ari Seff, Brian Cera, Dian Chen, Mason Ng, Aurick Zhou, Nigamaa Nayakanti, Khaled S Refaat, Rami Al-Rfou, and Benjamin Sapp · 2023
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Occworld: Learning a 3d occupancy world model for autonomous driving, 2023
Wenzhao Zheng, Weiliang Chen, Yuanhui Huang, Borui Zhang, Yueqi Duan, and Jiwen Lu · 2023
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Ye Yuan, Xinshuo Weng, Yanglan Ou, and Kris M Kitani · 2021
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Vista 2.0: An open, data-driven simulator for multimodal sensing and policy learning for autonomous vehicles
Alexander Amini, Tsun-Hsuan Wang, Igor Gilitschenski, Wilko Schwarting, Zhijian Liu, Song Han, Sertac Karaman, and Daniela Rus · 2022
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Beit: Bert pre-training of image transformers, 2022
Hangbo Bao, Li Dong, Songhao Piao, and Furu Wei · 2022
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Nuplan: A closed-loop ml-based planning benchmark for autonomous vehicles, 2022
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Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers
Zhiqi Li, Wenhai Wang, Hongyang Li, Enze Xie, Chonghao Sima, Tong Lu, Yu Qiao, and Jifeng Dai · 2022
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Zikang Zhou, Jianping Wang, Yung-Hui Li, and Yu-Kai Huang · 2023
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Vadv2: End-to-end vectorized autonomous driving via probabilistic planning
Shaoyu Chen, Bo Jiang, Hao Gao, Bencheng Liao, Qing Xu, Qian Zhang, Chang Huang, Wenyu Liu, and Xinggang Wang · 2024
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s 3 s^{3} gaussian: Self-supervised street gaussians for autonomous driving
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Street gaussians for modeling dynamic urban scenes
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Drivinggaussian: Composite gaussian splatting for surrounding dynamic autonomous driving scenes
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