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End-to-end motion planning models equipped with deep neural networks have shown great potential for enabling full autonomous driving.
The information bottleneck method
Naftali Tishby, Fernando C Pereira, and William Bialek · 2000
Earlier work this paper cites.
On self-distilling graph neural network
Yuzhao Chen, Yatao Bian, Xi Xiao, Yu Rong, Tingyang Xu, and Junzhou Huang · 2011
Earlier work this paper cites.
Rectifier nonlinearities improve neural network acoustic models
Andrew L Maas, Awni Y Hannun, Andrew Y Ng, et al · 2013
Earlier work this paper cites.
Optimizing the gaussian kernel function with the formulated kernel target alignment criterion for two-class pattern classification
Shangping Zhong, Daya Chen, Qiaofen Xu, and Tianshun Chen · 2013
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2015
Earlier work this paper cites.
Deep variational information bottleneck
Alexander A Alemi, Ian Fischer, Joshua V Dillon, and Kevin Murphy · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Learning efficient object detection models with knowledge distillation
Guobin Chen, Wongun Choi, Xiang Yu, Tony Han, and Manmohan Chandraker · 2017
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.
Grad-cam: Visual explanations from deep networks via gradient-based localization
Ramprasaath R Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
End-to-end learning of driving models from large-scale video datasets
Huazhe Xu, Yang Gao, Fisher Yu, and Trevor Darrell · 2017
Earlier work this paper cites.
Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer
Sergey Zagoruyko and Nikos Komodakis · 2017
Earlier work this paper cites.
Spatially-partitioned environmental representation and planning architecture for on-road autonomous driving
Wei Zhan, Jianyu Chen, Ching-Yao Chan, Changliu Liu, and Masayoshi Tomizuka · 2017
Earlier work this paper cites.
End-to-end driving via conditional imitation learning
Felipe Codevilla, Matthias Müller, Antonio López, Vladlen Koltun, and Alexey Dosovitskiy · 2018
Earlier work this paper cites.
Cirl: Controllable imitative reinforcement learning for vision-based self-driving
Xiaodan Liang, Tairui Wang, Luona Yang, and Eric Xing · 2018
Earlier work this paper cites.
Knowledge adaptation for efficient semantic segmentation
Tong He, Chunhua Shen, Zhi Tian, Dong Gong, Changming Sun, and Youliang Yan · 2019
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Structured knowledge distillation for semantic segmentation
Yifan Liu, Ke Chen, Chris Liu, Zengchang Qin, Zhenbo Luo, and Jingdong Wang · 2019
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Patient knowledge distillation for bert model compression
Siqi Sun, Yu Cheng, Zhe Gan, and Jingjing Liu · 2019
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Complex trajectory tracking using pid control for autonomous driving
Wael Farag · 2020
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Learning situational driving
Eshed Ohn-Bar, Aditya Prakash, Aseem Behl, Kashyap Chitta, and Andreas Geiger · 2020
Cited alongside, same era.
A survey of end-to-end driving: Architectures and training methods
End-to-end urban driving by imitating a reinforcement learning coach
Zhejun Zhang, Alexander Liniger, Dengxin Dai, Fisher Yu, and Luc Van Gool · 2021
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Learning from all vehicles
Dian Chen and Philipp Krähenbühl · 2022
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Bevdistill: Cross-modal bev distillation for multi-view 3d object detection
Zehui Chen, Zhenyu Li, Shiquan Zhang, Liangji Fang, Qinhong Jiang, and Feng Zhao · 2022
Later among the works it cites.
Freekd: Free-direction knowledge distillation for graph neural networks
Kaituo Feng, Changsheng Li, Ye Yuan, and Guoren Wang · 2022
Later among the works it cites.
Cross-modality knowledge distillation network for monocular 3d object detection
Yu Hong, Hang Dai, and Yong Ding · 2022
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Ardi Tampuu, Tambet Matiisen, Maksym Semikin, Dmytro Fishman, and Naveed Muhammad · 2020
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Mp3: A unified model to map, perceive, predict and plan
Sergio Casas, Abbas Sadat, and Raquel Urtasun · 2021
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Distilling knowledge via knowledge review
Pengguang Chen, Shu Liu, Hengshuang Zhao, and Jiaya Jia · 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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Lookout: Diverse multi-future prediction and planning for self-driving
Alexander Cui, Sergio Casas, Abbas Sadat, Renjie Liao, and Raquel Urtasun · 2021
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Lrc-bert: latent-representation contrastive knowledge distillation for natural language understanding
Hao Fu, Shaojun Zhou, Qihong Yang, Junjie Tang, Guiquan Liu, Kaikui Liu, and Xiaolong Li · 2021
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Instance-conditional knowledge distillation for object detection
Zijian Kang, Peizhen Zhang, Xiangyu Zhang, Jian Sun, and Nanning Zheng · 2021
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Shengchao Hu, Li Chen, Penghao Wu, Hongyang Li, Junchi Yan, and Dacheng Tao · 2022
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Glamd: Global and local attention mask distillation for object detectors
Younho Jang, Wheemyung Shin, Jinbeom Kim, Simon Woo, and Sung-Ho Bae · 2022
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Multi-granularity structural knowledge distillation for language model compression
Chang Liu, Chongyang Tao, Jiazhan Feng, and Dongyan Zhao · 2022
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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
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Focal and global knowledge distillation for detectors
Zhendong Yang, Zhe Li, Xiaohu Jiang, Yuan Gong, Zehuan Yuan, Danpei Zhao, and Chun Yuan · 2022
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Decoupled knowledge distillation
Borui Zhao, Quan Cui, Renjie Song, Yiyu Qiu, and Jiajun Liang · 2022
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Localization distillation for dense object detection
Zhaohui Zheng, Rongguang Ye, Ping Wang, Dongwei Ren, Wangmeng Zuo, Qibin Hou, and Ming-Ming Cheng · 2022
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https://leaderboard.carla.org/ , 2023
CARLA autonomous driving leaderboard · 2023
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Planning-oriented autonomous driving, 2023
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
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Safety-enhanced autonomous driving using interpretable sensor fusion transformer
Hao Shao, Letian Wang, Ruobing Chen, Hongsheng Li, and Yu Liu · 2023
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Policy pre-training for autonomous driving via self-supervised geometric modeling
Penghao Wu, Li Chen, Hongyang Li, Xiaosong Jia, Junchi Yan, and Yu Qiao · 2023
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Better teacher better student: Dynamic prior knowledge for knowledge distillation
Martin Zong, Zengyu Qiu, Xinzhu Ma, Kunlin Yang, Chunya Liu, Jun Hou, Shuai Yi, and Wanli Ouyang · 2023
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