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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

Modern autonomous vehicle perception systems are often constrained by occlusions, blind spots, and limited sensing range. While existing cooperative perception paradigms, such as Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I),…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Weijia Li , Haoen Xiang , Tianxu Wang , Shuaibing Wu , Qiming Xia , Cheng Wang , Chenglu Wen

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

Perception for automated driving is largely based on onboard environmental sensors, such as cameras and radar, which are cost-effective but limited by line-of-sight and field-of-view constraints. These inherent limitations may cause onboard…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Lukas Ostendorf , Lennart Reiher , Onn Haran , Lutz Eckstein

Autonomous trucking offers significant benefits, such as improved safety and reduced costs, but faces unique perception challenges due to trucks' large size and dynamic trailer movements. These challenges include extensive blind spots and…

Robotics · Computer Science 2025-08-11 Tenghui Xie , Zhiying Song , Fuxi Wen , Jun Li , Guangzhao Liu , Zijian Zhao

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

Vehicle-to-Vehicle (V2V) cooperative perception has great potential to enhance autonomous driving performance by overcoming perception limitations in complex adverse traffic scenarios (CATS). Meanwhile, data serves as the fundamental…

The comprehensiveness of vehicle-to-everything (V2X) recognition enriches and holistically shapes the global Birds-Eye-View (BEV) perception, incorporating rich semantics and integrating driving scene information, thereby serving features…

Robotics · Computer Science 2024-04-23 Fukang Li , Wenlin Ou , Kunpeng Gao , Yuwen Pang , Yifei Li , Henry Fan

Recent advancements in Vehicle-to-Everything (V2X) technologies have enabled autonomous vehicles to share sensing information to see through occlusions, greatly boosting the perception capability. However, there are no real-world datasets…

Computer Vision and Pattern Recognition · Computer Science 2024-12-18 Hao Xiang , Zhaoliang Zheng , Xin Xia , Runsheng Xu , Letian Gao , Zewei Zhou , Xu Han , Xinkai Ji , Mingxi Li , Zonglin Meng , Li Jin , Mingyue Lei , Zhaoyang Ma , Zihang He , Haoxuan Ma , Yunshuang Yuan , Yingqian Zhao , Jiaqi Ma

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

Vehicle-to-Everything (V2X) network has enabled collaborative perception in autonomous driving, which is a promising solution to the fundamental defect of stand-alone intelligence including blind zones and long-range perception. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-01 Ruiqing Mao , Jingyu Guo , Yukuan Jia , Yuxuan Sun , Sheng Zhou , Zhisheng Niu

With the advancement of collaborative perception, the role of aerial-ground collaborative perception, a crucial component, is becoming increasingly important. The demand for collaborative perception across different perspectives to…

Computer Vision and Pattern Recognition · Computer Science 2024-06-10 Yuchao Wang , Peirui Cheng , Pengju Tian , Ziyang Yuan , Liangjin Zhao , Jing Tian , Wensheng Wang , Zhirui Wang , Xian Sun

While Vehicle-to-Vehicle (V2V) collaboration extends sensing ranges through multi-agent data sharing, its reliability remains severely constrained by ground-level occlusions and the limited perspective of chassis-mounted sensors, which…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Xianke Wu , Songlin Bai , Chengxiang Li , Zhiyao Luo , Yulin Tian , Fenghua Zhu , Yisheng Lv , Yonglin Tian

With the tremendous advancement of deep learning and communication technology, Vehicle-to-Everything (V2X) cooperative perception has the potential to address limitations in sensing distant objects and occlusion for a single-agent…

Artificial Intelligence · Computer Science 2025-09-30 An Guo , Shuoxiao Zhang , Enyi Tang , Xinyu Gao , Haomin Pang , Haoxiang Tian , Yanzhou Mu , Wu Wen , Chunrong Fang , Zhenyu Chen

Modern perception systems of autonomous vehicles are known to be sensitive to occlusions and lack the capability of long perceiving range. It has been one of the key bottlenecks that prevents Level 5 autonomy. Recent research has…

Computer Vision and Pattern Recognition · Computer Science 2023-03-21 Runsheng Xu , Xin Xia , Jinlong Li , Hanzhao Li , Shuo Zhang , Zhengzhong Tu , Zonglin Meng , Hao Xiang , Xiaoyu Dong , Rui Song , Hongkai Yu , Bolei Zhou , Jiaqi Ma

Cooperative perception through vehicle-to-everything (V2X) has garnered significant attention in recent years due to its potential to overcome occlusions and enhance long-distance perception. Great achievements have been made in both…

Computer Vision and Pattern Recognition · Computer Science 2024-09-10 Rongsong Li , Xin Pei

Object detection is the central issue of intelligent traffic systems, and recent advancements in single-vehicle lidar-based 3D detection indicate that it can provide accurate position information for intelligent agents to make decisions and…

Artificial Intelligence · Computer Science 2023-10-11 Caizhen He , Hai Wang , Long Chen , Tong Luo , Yingfeng Cai

Due to the limitations of a single autonomous vehicle, Cellular Vehicle-to-Everything (C-V2X) technology opens a new window for achieving fully autonomous driving through sensor information sharing. However, real-world datasets supporting…

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

Modern autonomous vehicle perception systems often struggle with occlusions and limited perception range. Previous studies have demonstrated the effectiveness of cooperative perception in extending the perception range and overcoming…

Computer Vision and Pattern Recognition · Computer Science 2026-01-19 Lei Yang , Xinyu Zhang , Jun Li , Chen Wang , Jiaqi Ma , Zhiying Song , Tong Zhao , Ziying Song , Li Wang , Mo Zhou , Yang Shen , Kai Wu , Chen Lv
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