4 papers
OptiPMB: Enhancing 3D Multi-Object Tracking with Optimized Poisson Multi-Bernoulli Filtering
Guanhua Ding, Yuxuan Xia, Runwei Guan +5
Accurate 3D multi-object tracking (MOT) is crucial for autonomous driving, as it enables robust perception, navigation, and planning in complex environments. While deep learning-ba…
MMDrive: Interactive Scene Understanding Beyond Vision with Multi-representational Fusion
Minghui Hou, Wei-Hsing Huang, Shaofeng Liang +5
Vision-language models enable the understanding and reasoning of complex traffic scenarios through multi-source information fusion, establishing it as a core technology for autonom…
Large Foundation Models for Trajectory Prediction in Autonomous Driving: A Comprehensive Survey
Wei Dai, Shengen Wu, Wei Wu +7
Trajectory prediction serves as a critical functionality in autonomous driving, enabling the anticipation of future motion paths for traffic participants such as vehicles and pedes…
Cognitive Disentanglement for Referring Multi-Object Tracking
Shaofeng Liang, Runwei Guan, Wangwang Lian +6
As a significant application of multi-source information fusion in intelligent transportation perception systems, Referring Multi-Object Tracking (RMOT) involves localizing and tra…