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Zhenghao Peng
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2020 – today
- 2024
- [c15]Zhenghao Peng, Wenjie Luo, Yiren Lu, Tianyi Shen, Cole Gulino, Ari Seff, Justin Fu:
Improving Agent Behaviors with RL Fine-Tuning for Autonomous Driving. ECCV (25) 2024: 165-181 - [i21]Mingxin Huang, Dezhi Peng, Hongliang Li, Zhenghao Peng, Chongyu Liu, Dahua Lin, Yuliang Liu, Xiang Bai, Lianwen Jin:
SwinTextSpotter v2: Towards Better Synergy for Scene Text Spotting. CoRR abs/2401.07641 (2024) - [i20]Yunsong Zhou, Michael Simon
, Zhenghao Peng, Sicheng Mo, Hongzi Zhu, Minyi Guo, Bolei Zhou:
SimGen: Simulator-conditioned Driving Scene Generation. CoRR abs/2406.09386 (2024) - [i19]Brandon McMahan, Zhenghao Peng, Bolei Zhou, Jonathan C. Kao:
Shared Autonomy with IDA: Interventional Diffusion Assistance. CoRR abs/2409.15317 (2024) - [i18]Zhenghao Peng, Wenjie Luo, Yiren Lu, Tianyi Shen, Cole Gulino, Ari Seff, Justin Fu:
Improving Agent Behaviors with RL Fine-tuning for Autonomous Driving. CoRR abs/2409.18343 (2024) - 2023
- [j1]Quanyi Li, Zhenghao Peng
MetaDrive: Composing Diverse Driving Scenarios for Generalizable Reinforcement Learning. IEEE Trans. Pattern Anal. Mach. Intell. 45(3): 3461-3475 (2023) - [c14]Linrui Zhang, Zhenghao Peng, Quanyi Li, Bolei Zhou:
CAT: Closed-loop Adversarial Training for Safe End-to-End Driving. CoRL 2023: 2357-2372 - [c13]Zhenghai Xue, Zhenghao Peng, Quanyi Li, Zhihan Liu, Bolei Zhou:
Guarded Policy Optimization with Imperfect Online Demonstrations. ICLR 2023 - [c12]Lan Feng, Quanyi Li, Zhenghao Peng, Shuhan Tan, Bolei Zhou:
TrafficGen: Learning to Generate Diverse and Realistic Traffic Scenarios. ICRA 2023: 3567-3575 - [c11]Quanyi Li, Zhenghao Mark Peng, Lan Feng, Zhizheng Liu, Chenda Duan, Wenjie Mo, Bolei Zhou:
ScenarioNet: Open-Source Platform for Large-Scale Traffic Scenario Simulation and Modeling. NeurIPS 2023 - [c10]Zhenghao Mark Peng, Wenjie Mo, Chenda Duan, Quanyi Li, Bolei Zhou:
Learning from Active Human Involvement through Proxy Value Propagation. NeurIPS 2023 - [i17]Zhenghai Xue, Zhenghao Peng, Quanyi Li, Zhihan Liu, Bolei Zhou:
Guarded Policy Optimization with Imperfect Online Demonstrations. CoRR abs/2303.01728 (2023) - [i16]Quanyi Li, Zhenghao Peng, Lan Feng, Zhizheng Liu, Chenda Duan, Wenjie Mo, Bolei Zhou:
ScenarioNet: Open-Source Platform for Large-Scale Traffic Scenario Simulation and Modeling. CoRR abs/2306.12241 (2023) - [i15]Linrui Zhang, Zhenghao Peng, Quanyi Li, Bolei Zhou:
CAT: Closed-loop Adversarial Training for Safe End-to-End Driving. CoRR abs/2310.12432 (2023) - 2022
- [c9]Mingxin Huang
SwinTextSpotter: Scene Text Spotting via Better Synergy between Text Detection and Text Recognition. CVPR 2022: 4583-4593 - [c8]Qihang Zhang, Zhenghao Peng, Bolei Zhou:
Learning to Drive by Watching YouTube Videos: Action-Conditioned Contrastive Policy Pretraining. ECCV (26) 2022: 111-128 - [c7]Quanyi Li, Zhenghao Peng, Bolei Zhou:
Efficient Learning of Safe Driving Policy via Human-AI Copilot Optimization. ICLR 2022 - [c6]Boli Fang, Zhenghao Peng, Hao Sun, Qin Zhang
Meta Proximal Policy Optimization for Cooperative Multi-Agent Continuous Control. IJCNN 2022: 1-8 - [c5]Quanyi Li, Zhenghao Peng, Haibin Wu, Lan Feng, Bolei Zhou:
Human-AI Shared Control via Policy Dissection. NeurIPS 2022 - [i14]Quanyi Li, Zhenghao Peng, Bolei Zhou:
Efficient Learning of Safe Driving Policy via Human-AI Copilot Optimization. CoRR abs/2202.10341 (2022) - [i13]Mingxin Huang, Yuliang Liu, Zhenghao Peng, Chongyu Liu, Dahua Lin, Shenggao Zhu, Nicholas Jing Yuan, Kai Ding, Lianwen Jin:
SwinTextSpotter: Scene Text Spotting via Better Synergy between Text Detection and Text Recognition. CoRR abs/2203.10209 (2022) - [i12]Qihang Zhang, Zhenghao Peng, Bolei Zhou:
Action-Conditioned Contrastive Policy Pretraining. CoRR abs/2204.02393 (2022) - [i11]Quanyi Li, Zhenghao Peng, Haibin Wu, Lan Feng, Bolei Zhou:
Human-AI Shared Control via Frequency-based Policy Dissection. CoRR abs/2206.00152 (2022) - [i10]Lan Feng, Quanyi Li, Zhenghao Peng, Shuhan Tan, Bolei Zhou:
TrafficGen: Learning to Generate Diverse and Realistic Traffic Scenarios. CoRR abs/2210.06609 (2022) - 2021
- [c4]Zhenghao Peng, Quanyi Li, Chunxiao Liu, Bolei Zhou:
Safe Driving via Expert Guided Policy Optimization. CoRL 2021: 1554-1563 - [c3]Zhenghao Peng, Quanyi Li, Ka-Ming Hui, Chunxiao Liu, Bolei Zhou:
Learning to Simulate Self-driven Particles System with Coordinated Policy Optimization. NeurIPS 2021: 10784-10797 - [i9]Hao Sun, Ziping Xu, Meng Fang, Zhenghao Peng, Jiadong Guo, Bo Dai, Bolei Zhou:
Safe Exploration by Solving Early Terminated MDP. CoRR abs/2107.04200 (2021) - [i8]Quanyi Li, Zhenghao Peng, Zhenghai Xue, Qihang Zhang, Bolei Zhou:
MetaDrive: Composing Diverse Driving Scenarios for Generalizable Reinforcement Learning. CoRR abs/2109.12674 (2021) - [i7]Zhenghao Peng, Quanyi Li, Chunxiao Liu, Bolei Zhou:
Safe Driving via Expert Guided Policy Optimization. CoRR abs/2110.06831 (2021) - [i6]Zhenghao Peng, Quanyi Li, Ka-Ming Hui, Chunxiao Liu, Bolei Zhou:
Learning to Simulate Self-Driven Particles System with Coordinated Policy Optimization. CoRR abs/2110.13827 (2021) - 2020
- [i5]Hao Sun, Zhenghao Peng, Bo Dai, Jian Guo, Dahua Lin, Bolei Zhou:
Novel Policy Seeking with Constrained Optimization. CoRR abs/2005.10696 (2020) - [i4]Zhenghao Peng, Hao Sun, Bolei Zhou:
Non-local Policy Optimization via Diversity-regularized Collaborative Exploration. CoRR abs/2006.07781 (2020) - [i3]Quanyi Li, Zhenghao Peng, Qihang Zhang, Cong Qiu, Chunxiao Liu, Bolei Zhou:
Improving the Generalization of End-to-End Driving through Procedural Generation. CoRR abs/2012.13681 (2020)
2010 – 2019
- 2019
- [c2]Zhuoran Song, Ru Wang
Approximate Random Dropout for DNN training acceleration in GPGPU. DATE 2019: 108-113 - 2018
- [c1]Zhenghao Peng, Xuyang Chen, Chengwen Xu, Naifeng Jing, Xiaoyao Liang, Cewu Lu, Li Jiang:
AXNet: approximate computing using an end-to-end trainable neural network. ICCAD 2018: 11:1-11:8 - [i2]Zhuoran Song, Dongyu Ru, Ru Wang, Hongru Huang, Zhenghao Peng, Jing Ke, Xiaoyao Liang, Li Jiang:
Approximate Random Dropout. CoRR abs/1805.08939 (2018) - [i1]Zhenghao Peng, Xuyang Chen, Chengwen Xu, Naifeng Jing, Xiaoyao Liang, Cewu Lu, Li Jiang:
AXNet: ApproXimate computing using an end-to-end trainable neural network. CoRR abs/1807.10458 (2018)
Coauthor Index
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