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Modern autonomous driving systems are typically divided into three main tasks: perception, prediction, and planning.
Sgdr: Stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter · 2017
Earlier work this paper cites.
Fast and furious: Real time end-to-end 3d detection, tracking and motion forecasting with a single convolutional net
Wenjie Luo, Bin Yang, and Raquel Urtasun · 2018
Earlier work this paper cites.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2019
Earlier work this paper cites.
End-to-end interpretable neural motion planner
Wenyuan Zeng, Wenjie Luo, Simon Suo, Abbas Sadat, Bin Yang, Sergio Casas, and Raquel Urtasun · 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.
Pnpnet: End-to-end perception and prediction with tracking in the loop
Ming Liang, Bin Yang, Wenyuan Zeng, Yun Chen, Rui Hu, Sergio Casas, and Raquel Urtasun · 2020
Earlier work this paper cites.
Perceive, predict, and plan: Safe motion planning through interpretable semantic representations
Abbas Sadat, Sergio Casas, Mengye Ren, Xinyu Wu, Pranaab Dhawan, and Raquel Urtasun · 2020
Cited alongside, same era.
What data do we need for training an AV motion planner?
Long Chen, Lukas Platinsky, Stefanie Speichert, Blazej Osinski, Oliver Scheel, Yawei Ye, Hugo Grimmett, Luca Del Pero, and Peter Ondruska · 2021
Cited alongside, same era.
Densetnt: End-to-end trajectory prediction from dense goal sets
Junru Gu, Chen Sun, and Hang Zhao · 2021
Cited alongside, same era.
FIERY: Future instance segmentation 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
Cited alongside, same era.
Safe local motion planning with self-supervised freespace forecasting
Peiyun Hu, Aaron Huang, John Dolan, David Held, and Deva Ramanan · 2021
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
Later among the works it cites.
Differentiable raycasting for self-supervised occupancy forecasting
Tarasha Khurana, Peiyun Hu, Achal Dave, Jason Ziglar, David Held, and Deva Ramanan · 2022
Later among the works it cites.
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
Later among the works it cites.
Planning-oriented autonomous driving
Yihan Hu, Jiazhi Yang, Li Chen, Keyu Li, Chonghao Sima, Xizhou Zhu, Siqi Chai, Senyao Du, Tianwei Lin, Wenhai Wang, Lewei Lu, Xiaosong Jia, Qiang Liu, Jifeng Dai, Yu Qiao, and Hongyang Li · 2023
Closest in time.
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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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.
Closest in time.
Cape: Camera view position embedding for multi-view 3d object detection
Kaixin Xiong, Shi Gong, Xiaoqing Ye, Xiao Tan, Ji Wan, Errui Ding, Jingdong Wang, and Xiang Bai · 2023
Closest in time.