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Vehicle-to-everything technologies (V2X) have become an ideal paradigm to extend the perception range and see through the occlusion. Exiting efforts focus on single-frame cooperative perception, however, how to capture the temporal cue…

Machine Learning · Computer Science 2025-11-04 Xinyu Zhang , Zewei Zhou , Zhaoyi Wang , Yangjie Ji , Yanjun Huang , Hong Chen

Multi-view cooperative perception and multimodal fusion are essential for reliable 3D spatiotemporal understanding in autonomous driving, especially under occlusions, limited viewpoints, and communication delays in V2X scenarios. This paper…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Zhenwei Yang , Yibo Ai , Weidong Zhang

In this paper, we investigate the application of Vehicle-to-Everything (V2X) communication to improve the perception performance of autonomous vehicles. We present a robust cooperative perception framework with V2X communication using a…

Computer Vision and Pattern Recognition · Computer Science 2022-08-09 Runsheng Xu , Hao Xiang , Zhengzhong Tu , Xin Xia , Ming-Hsuan Yang , Jiaqi Ma

Cooperative perception through Vehicle-to-Everything (V2X) communication offers significant potential for enhancing vehicle perception by mitigating occlusions and expanding the field of view. However, past research has predominantly…

Computer Vision and Pattern Recognition · Computer Science 2025-09-05 Seth Z. Zhao , Huizhi Zhang , Zhaowei Li , Juntong Peng , Anthony Chui , Zewei Zhou , Zonglin Meng , Hao Xiang , Zhiyu Huang , Fujia Wang , Ran Tian , Chenfeng Xu , Bolei Zhou , Jiaqi Ma

Predicting future trajectories of surrounding traffic agents is critical for safe autonomous navigation and collision avoidance. Despite all advances in the trajectory forecasting realm, the prediction models remains vulnerable to…

Vehicle-to-everything (V2X) perception is an innovative technology that enhances vehicle perception accuracy, thereby elevating the security and reliability of autonomous systems. However, existing V2X perception methods focus on static…

Computer Vision and Pattern Recognition · Computer Science 2023-10-31 Jiayao Tan , Fan Lyu , Linyan Li , Fuyuan Hu , Tingliang Feng , Fenglei Xu , Rui Yao

V2X cooperation, through the integration of sensor data from both vehicles and infrastructure, is considered a pivotal approach to advancing autonomous driving technology. Current research primarily focuses on enhancing perception accuracy,…

Computer Vision and Pattern Recognition · Computer Science 2024-05-08 Zhiwei Li , Bozhen Zhang , Lei Yang , Tianyu Shen , Nuo Xu , Ruosen Hao , Weiting Li , Tao Yan , Huaping Liu

Cooperative perception extends the perception capabilities of autonomous vehicles by enabling multi-agent information sharing via Vehicle-to-Everything (V2X) communication. Unlike traditional onboard sensors, V2X acts as a dynamic…

Other Computer Science · Computer Science 2025-05-05 Zhiying Song , Tenghui Xie , Fuxi Wen , Jun Li

Cooperative perception enabled by Vehicle-to-Everything (V2X) communication holds significant promise for enhancing the perception capabilities of autonomous vehicles, allowing them to overcome occlusions and extend their field of view.…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Hao Xiang , Zhaoliang Zheng , Xin Xia , Seth Z. Zhao , Letian Gao , Zewei Zhou , Tianhui Cai , Yun Zhang , Jiaqi Ma

The paper addresses the vehicle-to-X (V2X) data fusion for cooperative or collective perception (CP). This emerging and promising intelligent transportation systems (ITS) technology has enormous potential for improving efficiency and safety…

Vehicle-to-everything (V2X) autonomous driving opens up a promising direction for developing a new generation of intelligent transportation systems. Collaborative perception (CP) as an essential component to achieve V2X can overcome the…

Computer Vision and Pattern Recognition · Computer Science 2023-09-01 Si Liu , Chen Gao , Yuan Chen , Xingyu Peng , Xianghao Kong , Kun Wang , Runsheng Xu , Wentao Jiang , Hao Xiang , Jiaqi Ma , Miao Wang

Occlusion is a major challenge for LiDAR-based object detection methods. This challenge becomes safety-critical in urban traffic where the ego vehicle must have reliable object detection to avoid collision while its field of view is…

Robotics · Computer Science 2023-09-20 Minh-Quan Dao , Julie Stephany Berrio , Vincent Frémont , Mao Shan , Elwan Héry , Stewart Worrall

Cooperative perception enabled by Vehicle-to-Everything (V2X) communication enhances autonomous driving safety by creating a unified environmental representation through shared sensory data. While recent works have advanced multi-agent…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Abhishek Dinkar Jagtap , Sanath Tiptur Sadashivaiah , Andreas Festag

Vehicle-to-Everything (V2X) collaborative perception extends sensing beyond single vehicle limits through transmission. However, as more agents participate, existing frameworks face two key challenges: (1) the participating agents are…

Computer Vision and Pattern Recognition · Computer Science 2025-11-14 Yueran Zhao , Zhang Zhang , Chao Sun , Tianze Wang , Chao Yue , Nuoran Li

The objective of the collaborative vehicle-to-everything perception task is to enhance the individual vehicle's perception capability through message communication among neighboring traffic agents. Previous methods focus on achieving…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Si Liu , Zihan Ding , Jiahui Fu , Hongyu Li , Siheng Chen , Shifeng Zhang , Xu Zhou

Connected Autonomous Vehicles (CAVs) benefit from Vehicle-to-Everything (V2X) communication, which enables the exchange of sensor data to achieve Collaborative Perception (CP). To reduce cumulative errors in perception modules and mitigate…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Lei Wan , Hannan Ejaz Keen , Alexey Vinel

Autonomous driving holds transformative potential but remains fundamentally constrained by the limited perception and isolated decision-making with standalone intelligence. While recent multi-agent approaches introduce cooperation, they…

Robotics · Computer Science 2025-11-13 Ziyi Song , Chen Xia , Chenbing Wang , Haibao Yu , Sheng Zhou , Zhisheng Niu

Vehicle-to-everything (V2X) communication techniques enable the collaboration between vehicles and many other entities in the neighboring environment, which could fundamentally improve the perception system for autonomous driving. However,…

Computer Vision and Pattern Recognition · Computer Science 2022-07-19 Yiming Li , Dekun Ma , Ziyan An , Zixun Wang , Yiqi Zhong , Siheng Chen , Chen Feng

Cooperatively utilizing both ego-vehicle and infrastructure sensor data via V2X communication has emerged as a promising approach for advanced autonomous driving. However, current research mainly focuses on improving individual modules,…

Robotics · Computer Science 2024-12-25 Haibao Yu , Wenxian Yang , Jiaru Zhong , Zhenwei Yang , Siqi Fan , Ping Luo , Zaiqing Nie

With the rapid advancement of autonomous driving technology, vehicle-to-everything (V2X) communication has emerged as a key enabler for extending perception range and enhancing driving safety by providing visibility beyond the line of…

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