Jun Guo

According to our database, Jun Guo authored at least 15 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

FlowDreamer: A RGB-D World Model with Flow-based Motion Representations for Robot Manipulation.

Jun Guo, Xiaojian Ma, Yikai Wang, Min Yang, Huaping Liu, Qing Li

CoRR, May, 2025

Embodied VideoAgent: Persistent Memory from Egocentric Videos and Embodied Sensors Enables Dynamic Scene Understanding.

Yue Fan, Xiaojian Ma, Rongpeng Su, Jun Guo, Rujie Wu, Xi Chen, Qing Li

CoRR, January, 2025

Attacking cooperative multi-agent reinforcement learning by adversarial minority influence.

Simin Li, Jun Guo, Jingqiao Xiu, Yuwei Zheng, Pu Feng, Xin Yu, Jiakai Wang, Aishan Liu, Yaodong Yang, Bo An, Wenjun Wu, Xianglong Liu

Neural Networks, 2025

2024

Generate Transferable Adversarial Physical Camouflages via Triplet Attention Suppression.

Jiakai Wang, Xianglong Liu, Zixin Yin, Yuxuan Wang, Jun Guo, Haotong Qin, Qingtao Wu, Aishan Liu

Int. J. Comput. Vis., November, 2024

Semantic Gaussians: Open-Vocabulary Scene Understanding with 3D Gaussian Splatting.

Jun Guo, Xiaojian Ma, Yue Fan, Huaping Liu, Qing Li

CoRR, 2024

Byzantine Robust Cooperative Multi-Agent Reinforcement Learning as a Bayesian Game.

Simin Li, Jun Guo, Jingqiao Xiu, Ruixiao Xu, Xin Yu, Jiakai Wang, Aishan Liu, Yaodong Yang, Xianglong Liu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

A comprehensive evaluation framework for deep model robustness.

Jun Guo, Wei Bao, Jiakai Wang, Yuqing Ma, Xinghai Gao, Gang Xiao, Aishan Liu, Jian Dong, Xianglong Liu, Wenjun Wu

Pattern Recognit., May, 2023

MIR2: Towards Provably Robust Multi-Agent Reinforcement Learning by Mutual Information Regularization.

Simin Li, Ruixiao Xu, Jun Guo, Pu Feng, Jiakai Wang, Aishan Liu, Yaodong Yang, Xianglong Liu, Weifeng Lv

CoRR, 2023

Byzantine Robust Cooperative Multi-Agent Reinforcement Learning as a Bayesian Game.

Simin Li, Jun Guo, Jingqiao Xiu, Xini Yu, Jiakai Wang, Aishan Liu, Yaodong Yang, Xianglong Liu

CoRR, 2023

Attacking Cooperative Multi-Agent Reinforcement Learning by Adversarial Minority Influence.

Simin Li, Jun Guo, Jingqiao Xiu, Pu Feng, Xin Yu, Jiakai Wang, Aishan Liu, Wenjun Wu, Xianglong Liu

CoRR, 2023

X-Adv: Physical Adversarial Object Attacks against X-ray Prohibited Item Detection.

Aishan Liu, Jun Guo, Jiakai Wang, Siyuan Liang, Renshuai Tao, Wenbo Zhou, Cong Liu, Xianglong Liu, Dacheng Tao

Proceedings of the 32nd USENIX Security Symposium, 2023

Isolation and Induction: Training Robust Deep Neural Networks against Model Stealing Attacks.

Jun Guo, Xingyu Zheng, Aishan Liu, Siyuan Liang, Yisong Xiao, Yichao Wu, Xianglong Liu

Proceedings of the 31st ACM International Conference on Multimedia, 2023

2022

Towards Comprehensive Testing on the Robustness of Cooperative Multi-agent Reinforcement Learning.

Jun Guo, Yonghong Chen, Yihang Hao, Zixin Yin, Yin Yu, Simin Li

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021

A Comprehensive Evaluation Framework for Deep Model Robustness.

Aishan Liu, Xianglong Liu, Jun Guo, Jiakai Wang, Yuqing Ma, Ze Zhao, Xinghai Gao, Gang Xiao

CoRR, 2021

Improving Generalization of Deepfake Detection with Domain Adaptive Batch Normalization.

Zixin Yin, Jiakai Wang, Yifu Ding, Yisong Xiao, Jun Guo, Renshuai Tao, Haotong Qin

Proceedings of the ADVM '21: Proceedings of the 1st International Workshop on Adversarial Learning for Multimedia, 2021