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End-to-end autonomous driving (E2E-AD) has emerged as a trend in the field of autonomous driving, promising a data-driven, scalable approach to system design.
nuscenes: A multimodal dataset for autonomous driving, 2020a
Holger Caesar, Varun Bankiti, Alex H. Lang, Sourabh Vora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom · 1903
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Alvinn: An autonomous land vehicle in a neural network
Dean A Pomerleau · 1988
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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 · 2005
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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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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Attention is all you need
Ashish Vaswani, Noam M. Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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End-to-end driving via conditional imitation learning
Felipe Codevilla, Matthias Müller, Antonio López, Vladlen Koltun, and Alexey Dosovitskiy · 2018
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Exploring the limitations of behavior cloning for autonomous driving
Felipe Codevilla, Eder Santana, Antonio M López, and Adrien Gaidon · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever · 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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End-to-end object detection with transformers, 2020
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
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Learning by cheating
Dian Chen, Brady Zhou, Vladlen Koltun, and Philipp Krähenbühl · 2020
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Learning lane graph representations for motion forecasting
Ming Liang, Bin Yang, Rui Hu, Yun Chen, Renjie Liao, Song Feng, and Raquel Urtasun · 2020
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Learning to evaluate perception models using planner-centric metrics
Jonah Philion, Amlan Kar, and Sanja Fidler · 2020
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Pointpainting: sequential fusion for 3d object detection
Sourabh Vora, Alex H Lang, Bassam Helou, and Oscar Beijbom · 2020
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Safe local motion planning with self-supervised freespace forecasting
Peiyun Hu, Aaron Huang, John Dolan, David Held, and Deva Ramanan · 2021
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Ide-net: Interactive driving event and pattern extraction from human data
Xiaosong Jia, Liting Sun, Masayoshi Tomizuka, and Wei Zhan · 2021
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Multi-modal fusion transformer for end-to-end autonomous driving
Aditya Prakash, Kashyap Chitta, and Andreas Geiger · 2021
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Learning from all vehicles
Dian Chen and Philipp Krähenbühl · 2022
Cited alongside, same era.
Persformer: 3d lane detection via perspective transformer and the openlane benchmark
Li Chen, Chonghao Sima, Yang Li, Zehan Zheng, Jiajie Xu, Xiangwei Geng, Hongyang Li, Conghui He, Jianping Shi, Yu Qiao, and Junchi Yan · 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.
Multi-agent trajectory prediction by combining egocentric and allocentric views
Xiaosong Jia, Liting Sun, Hang Zhao, Masayoshi Tomizuka, and Wei Zhan · 2022
Cited alongside, same era.
Differentiable raycasting for self-supervised occupancy forecasting
Tarasha Khurana, Peiyun Hu, Achal Dave, Jason Ziglar, David Held, and Deva Ramanan · 2022
Cited alongside, same era.
Maptr: Structured modeling and learning for online vectorized hd map construction
Bencheng Liao, Shaoyu Chen, Xinggang Wang, Tianheng Cheng, Qian Zhang, Wenyu Liu, and Chang Huang · 2023
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Time will tell: New outlooks and a baseline for temporal multi-view 3d object detection
Jinhyung Park, Chenfeng Xu, Shijia Yang, Kurt Keutzer, Kris Kitani, Masayoshi Tomizuka, and Wei Zhan · 2023
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Reasonnet: End-to-end driving with temporal and global reasoning
Hao Shao, Letian Wang, Ruobing Chen, Steven L Waslander, Hongsheng Li, and Yu Liu · 2023
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Exploring object-centric temporal modeling for efficient multi-view 3d object detection
Shihao Wang, Yingfei Liu, Tiancai Wang, Ying Li, and Xiangyu Zhang · 2023
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Robobev: Towards robust bird’s eye view perception under corruptions
Shaoyuan Xie, Lingdong Kong, Wenwei Zhang, Jiawei Ren, Liang Pan, Kai Chen, and Ziwei Liu · 2023
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William Peebles and Saining Xie · 2022
Cited alongside, same era.
Plant: explainable planning transformers via object-level representations
Katrin Renz, Kashyap Chitta, Otniel-Bogdan Mercea, A. Sophia Koepke, Zeynep Akata, and Andreas Geiger · 2022
Cited alongside, same era.
Safety-enhanced autonomous driving using interpretable sensor fusion transformer
Hao Shao, Letian Wang, RuoBing Chen, Hongsheng Li, and Yu Liu · 2022
Cited alongside, same era.
Whose track is it anyway? improving robustness to tracking errors with affinity-based trajectory prediction
Xinshuo Weng, Boris Ivanovic, Kris Kitani, and Marco Pavone · 2022
Cited alongside, same era.
Trajectory-guided control prediction for end-to-end autonomous driving: A simple yet strong baseline
Penghao Wu, Xiaosong Jia, Li Chen, Junchi Yan, Hongyang Li, and Yu Qiao · 2022
Cited alongside, same era.
Motr: End-to-end multiple-object tracking with transformer
Fangao Zeng, Bin Dong, Yuang Zhang, Tiancai Wang, Xiangyu Zhang, and Yichen Wei · 2022
Cited alongside, same era.
Mmfn: multi-modal-fusion-net for end-to-end driving
Qingwen Zhang, Mingkai Tang, Ruoyu Geng, Feiyi Chen, Ren Xin, and Lujia Wang · 2022
Cited alongside, same era.
Rethinking the open-loop evaluation of end-to-end autonomous driving in nuscenes
Jiang-Tian Zhai, Ze Feng, Jihao Du, Yongqiang Mao, Jiang-Jiang Liu, Zichang Tan, Yifu Zhang, Xiaoqing Ye, and Jingdong Wang · 2023
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Eva-02: A visual representation for neon genesis
Yuxin Fang, Quan Sun, Xinggang Wang, Tiejun Huang, Xinlong Wang, and Yue Cao · 2024
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Bench2drive: Towards multi-ability benchmarking of closed-loop end-to-end autonomous driving
Xiaosong Jia, Zhenjie Yang, Qifeng Li, Zhiyuan Zhang, and Junchi Yan · 2024
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Far3d: Expanding the horizon for surround-view 3d object detection
Xiaohui Jiang, Shuailin Li, Yingfei Liu, Shihao Wang, Fan Jia, Tiancai Wang, Lijin Han, and Xiangyu Zhang · 2024
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Leveraging enhanced queries of point sets for vectorized map construction
Zihao Liu, Xiaoyu Zhang, Guangwei Liu, Ji Zhao, and Ningyi Xu · 2024
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Activead: Planning-oriented active learning for end-to-end autonomous driving, 2024
Han Lu, Xiaosong Jia, Yichen Xie, Wenlong Liao, Xiaokang Yang, and Junchi Yan · 2024
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Shaoshuai Shi, Li Jiang, Dengxin Dai, and Bernt Schiele · 2024
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Haisheng Su, Wei Wu, and Junchi Yan · 2024
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Sparsedrive: End-to-end autonomous driving via sparse scene representation, 2024
Wenchao Sun, Xuewu Lin, Yining Shi, Chuang Zhang, Haoran Wu, and Sifa Zheng · 2024
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Para-drive: Parallelized architecture for real-time autonomous driving
Xinshuo Weng, Boris Ivanovic, Yan Wang, Yue Wang, and Marco Pavone · 2024
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Sparsead: Sparse query-centric paradigm for efficient end-to-end autonomous driving, 2024
Diankun Zhang, Guoan Wang, Runwen Zhu, Jianbo Zhao, Xiwu Chen, Siyu Zhang, Jiahao Gong, Qibin Zhou, Wenyuan Zhang, Ningzi Wang, Feiyang Tan, Hangning Zhou, Ziyao Xu, Haotian Yao, Chi Zhang, Xiaojun Liu, Xiaoguang Di, and Bin Li · 2024
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End-to-end urban driving by imitating a reinforcement learning coach
Zhejun Zhang, Alexander Liniger, Dengxin Dai, Fisher Yu, and Luc Van Gool · 2024
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