3 papers
cs.CV2025
SemanticFlow: A Self-Supervised Framework for Joint Scene Flow Prediction and Instance Segmentation in Dynamic Environments
Yinqi Chen, Meiying Zhang, Qi Hao +1
Accurate perception of dynamic traffic scenes is crucial for high-level autonomous driving systems, requiring robust object motion estimation and instance segmentation. However, tr…
cs.RO2025
SSF-PAN: Semantic Scene Flow-Based Perception for Autonomous Navigation in Traffic Scenarios
Yinqi Chen, Meiying Zhang, Qi Hao +1
Vehicle detection and localization in complex traffic scenarios pose significant challenges due to the interference of moving objects. Traditional methods often rely on outlier exc…
cs.CV2024
TSceneJAL: Joint Active Learning of Traffic Scenes for 3D Object Detection
Chenyang Lei, Weiyuan Peng, Guang Zhou +4
Most autonomous driving (AD) datasets incur substantial costs for collection and labeling, inevitably yielding a plethora of low-quality and redundant data instances, thereby compr…