7 citations · 17 across the 14 of their papers we have counts for
11 papers · 1 filter
ChatDyn: Language-Driven Multi-Actor Dynamics Generation in Street Scenes
Yuxi Wei, Jingbo Wang, Yuwen Du +6
Generating realistic and interactive dynamics of traffic participants according to specific instruction is critical for street scene simulation. However, there is currently a lack…
InfiniCube: Unbounded and Controllable Dynamic 3D Driving Scene Generation with World-Guided Video Models
Yifan Lu, Xuanchi Ren, Jiawei Yang +8
We present InfiniCube, a scalable method for generating unbounded dynamic 3D driving scenes with high fidelity and controllability. Previous methods for scene generation either suf…
Self-Evolving Multi-Agent Collaboration Networks for Software Development
Yue Hu, Yuzhu Cai, Yaxin Du +6
LLM-driven multi-agent collaboration (MAC) systems have demonstrated impressive capabilities in automatic software development at the function level. However, their heavy reliance…
Communication-Efficient Collaborative Perception via Information Filling with Codebook
Yue Hu, Juntong Peng, Sifei Liu +3
Collaborative perception empowers each agent to improve its perceptual ability through the exchange of perceptual messages with other agents. It inherently results in a fundamental…
Ethical-Lens: Curbing Malicious Usages of Open-Source Text-to-Image Models
Yuzhu Cai, Sheng Yin, Yuxi Wei +5
The burgeoning landscape of text-to-image models, exemplified by innovations such as Midjourney and DALLE 3, has revolutionized content creation across diverse sectors. However, th…
Towards Collaborative Autonomous Driving: Simulation Platform and End-to-End System
Genjia Liu, Yue Hu, Chenxin Xu +8
Vehicle-to-everything-aided autonomous driving (V2X-AD) has a huge potential to provide a safer driving solution. Despite extensive researches in transportation and communication t…
V2X-PC: Vehicle-to-everything Collaborative Perception via Point Cluster
Si Liu, Zihan Ding, Jiahui Fu +4
The objective of the collaborative vehicle-to-everything perception task is to enhance the individual vehicle's perception capability through message communication among neighborin…
Editable Scene Simulation for Autonomous Driving via Collaborative LLM-Agents
Yuxi Wei, Zi Wang, Yifan Lu +5
Scene simulation in autonomous driving has gained significant attention because of its huge potential for generating customized data. However, existing editable scene simulation ap…
Self-Alignment of Large Language Models via Monopolylogue-based Social Scene Simulation
Xianghe Pang, Shuo Tang, Rui Ye +4
Aligning large language models (LLMs) with human values is imperative to mitigate potential adverse effects resulting from their misuse. Drawing from the sociological insight that…
Pragmatic Communication in Multi-Agent Collaborative Perception
Yue Hu, Xianghe Pang, Xiaoqi Qin +4
Collaborative perception allows each agent to enhance its perceptual abilities by exchanging messages with others. It inherently results in a trade-off between perception ability a…
An Extensible Framework for Open Heterogeneous Collaborative Perception
Yifan Lu, Yue Hu, Yiqi Zhong +3
Collaborative perception aims to mitigate the limitations of single-agent perception, such as occlusions, by facilitating data exchange among multiple agents. However, most current…