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End-to-end (E2E) autonomous driving (AD) models require diverse, high-quality data to perform well across various driving scenarios.
Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography
Martin A. Fischler and Robert C. Bolles · 1981
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A review of motion planning techniques for automated vehicles
David González, Joshué Pérez, Vicente Milanés, and Fawzi Nashashibi · 2015
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An introduction to Unreal engine 4
Andrew Sanders · 2016
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Carla: An open urban driving simulator
Alexey Dosovitskiy, German Ros, Felipe Codevilla, Antonio Lopez, and Vladlen Koltun · 2017
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Learning to drive in a day
Alex Kendall, Jeffrey Hawke, David Janz, Przemyslaw Mazur, Daniele Reda, John-Mark Allen, Vinh-Dieu Lam, Alex Bewley, and Amar Shah · 2019
Earlier work this paper cites.
nuscenes: A multimodal dataset for autonomous driving
Holger Caesar, Varun Bankiti, Alex H Lang, Sourabh Vora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom · 2020
Earlier work this paper 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
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nuplan: A closed-loop ml-based planning benchmark for autonomous vehicles
Holger Caesar, Juraj Kabzan, Kok Seang Tan, Whye Kit Fong, Eric Wolff, Alex Lang, Luke Fletcher, Oscar Beijbom, and Sammy Omari · 2021
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What data do we need for training an av motion planner?
Long Chen, Lukas Platinsky, Stefanie Speichert, Błażej Osiński, Oliver Scheel, Yawei Ye, Hugo Grimmett, Luca Del Pero, and Peter Ondruska · 2021
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Neat: Neural attention fields for end-to-end autonomous driving
Kashyap Chitta, Aditya Prakash, and Andreas Geiger · 2021
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Fiery: Future instance prediction in bird’s-eye view from surround monocular cameras
Anthony Hu, Zak Murez, Nikhil Mohan, Sofía Dudas, Jeffrey Hawke, Vijay Badrinarayanan, Roberto Cipolla, and Alex Kendall · 2021
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Autonomous vehicle motion planning via recurrent spline optimization
Wenda Xu, Qian Wang, and John M Dolan · 2021
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Exploring data augmentation for multi-modality 3d object detection, 2021
Wenwei Zhang, Zhe Wang, and Chen Change Loy · 2021
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Vehicle trajectory prediction works, but not everywhere
Mohammadhossein Bahari, Saeed Saadatnejad, Ahmad Rahimi, Mohammad Shaverdikondori, Amir Hossein Shahidzadeh, Seyed-Mohsen Moosavi-Dezfooli, and Alexandre Alahi · 2022
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Learning from all vehicles
Dian Chen and Philipp Krähenbühl · 2022
Cited alongside, same era.
Transfuser: Imitation with transformer-based sensor fusion for autonomous driving
Kashyap Chitta, Aditya Prakash, Bernhard Jaeger, Zehao Yu, Katrin Renz, and Andreas Geiger · 2022
Cited alongside, same era.
King: Generating safety-critical driving scenarios for robust imitation via kinematics gradients
Niklas Hanselmann, Katrin Renz, Kashyap Chitta, Apratim Bhattacharyya, and Andreas Geiger · 2022
Cited alongside, same era.
St-p3: End-to-end vision-based autonomous driving via spatial-temporal feature learning
Shengchao Hu, Li Chen, Penghao Wu, Hongyang Li, Junchi Yan, and Dacheng Tao · 2022
Cited alongside, same era.
Plant: Explainable planning transformers via object-level representations
Katrin Renz, Kashyap Chitta, Otniel-Bogdan Mercea, A Koepke, Zeynep Akata, and Andreas Geiger · 2022
Cited alongside, same era.
Syndiff-ad: Improving semantic segmentation and end-to-end autonomous driving with synthetic data from latent diffusion models, 2024
Harsh Goel, Sai Shankar Narasimhan, Oguzhan Akcin, and Sandeep Chinchali · 2024
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Are nerfs ready for autonomous driving? towards closing the real-to-simulation gap
Carl Lindström, Georg Hess, Adam Lilja, Maryam Fatemi, Lars Hammarstrand, Christoffer Petersson, and Lennart Svensson · 2024
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Towards collaborative autonomous driving: Simulation platform and end-to-end system
Genjia Liu, Yue Hu, Chenxin Xu, Weibo Mao, Junhao Ge, Zhengxiang Huang, Yifan Lu, Yinda Xu, Junkai Xia, Yafei Wang, et al · 2024
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Unleashing generalization of end-to-end autonomous driving with controllable long video generation
Enhui Ma, Lijun Zhou, Tao Tang, Zhan Zhang, Dong Han, Junpeng Jiang, Kun Zhan, Peng Jia, Xianpeng Lang, Haiyang Sun, et al · 2024
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Gri: General reinforced imitation and its application to vision-based autonomous driving
Raphael Chekroun, Marin Toromanoff, Sascha Hornauer, and Fabien Moutarde · 2023
Cited alongside, same era.
Re-evaluating lidar scene flow for autonomous driving, 2023
Nathaniel Chodosh, Deva Ramanan, and Simon Lucey · 2023
Cited alongside, same era.
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
Cited alongside, same era.
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
Cited alongside, same era.
3d gaussian splatting for real-time radiance field rendering
Bernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, and George Drettakis · 2023
Cited alongside, same era.
Rethinking the open-loop evaluation of end-to-end autonomous driving in nuscenes
Jiang-Tian Zhai, Ze Feng, Jinhao Du, Yongqiang Mao, Jiang-Jiang Liu, Zichang Tan, Yifu Zhang, Xiaoqing Ye, and Jingdong Wang · 2023
Cited alongside, same era.
S-nerf++: Autonomous driving simulation via neural reconstruction and generation
Yurui Chen, Junge Zhang, Ziyang Xie, Wenye Li, Feihu Zhang, Jiachen Lu, and Li Zhang · 2024
Cited alongside, same era.
Zhongjian Qiao, Jiafei Lyu, Kechen Jiao, Qi Liu, and Xiu Li · 2024
Later among the works it cites.
BlenderNeRF, 2024
Maxime Raafat · 2024
Later among the works it cites.
Street-view image generation from a bird’s-eye view layout
Alexander Swerdlow, Runsheng Xu, and Bolei Zhou · 2024
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3d data augmentation for driving scenes on camera
Wenwen Tong, Jiangwei Xie, Tianyu Li, Yang Li, Hanming Deng, Bo Dai, Lewei Lu, Hao Zhao, Junchi Yan, and Hongyang Li · 2024
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Panacea: Panoramic and controllable video generation for autonomous driving
Yuqing Wen, Yucheng Zhao, Yingfei Liu, Fan Jia, Yanhui Wang, Chong Luo, Chi Zhang, Tiancai Wang, Xiaoyan Sun, and Xiangyu Zhang · 2024
Later among the works it cites.
Drivearena: A closed-loop generative simulation platform for autonomous driving
Xuemeng Yang, Licheng Wen, Yukai Ma, Jianbiao Mei, Xin Li, Tiantian Wei, Wenjie Lei, Daocheng Fu, Pinlong Cai, Min Dou, et al · 2024
Later among the works it cites.
Hugsim: A real-time, photo-realistic and closed-loop simulator for autonomous driving
Hongyu Zhou, Longzhong Lin, Jiabao Wang, Yichong Lu, Dongfeng Bai, Bingbing Liu, Yue Wang, Andreas Geiger, and Yiyi Liao · 2024
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Safe-sim: Safety-critical closed-loop traffic simulation with diffusion-controllable adversaries
Wei-Jer Chang, Francesco Pittaluga, Masayoshi Tomizuka, Wei Zhan, and Manmohan Chandraker · 2025
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Neuroncap: Photorealistic closed-loop safety testing for autonomous driving
William Ljungbergh, Adam Tonderski, Joakim Johnander, Holger Caesar, Kalle Åström, Michael Felsberg, and Christoffer Petersson · 2025
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