OOSTraj: Out-of-Sight Trajectory Prediction With Vision-Positioning Denoising

arXiv:2404.02227v1 Announce Type: cross
Abstract: Trajectory prediction is fundamental in computer vision and autonomous driving, particularly for understanding pedestrian behavior and enabling proactive decision-making. Existing approaches in this field often assume precise and complete observational data, neglecting the challenges associated with out-of-view objects and the noise inherent in sensor data due to limited camera range, physical obstructions, and the absence of ground truth for denoised sensor data. Such oversights are critical safety concerns, as they can result in missing essential, …

arxiv cs.ai cs.cv cs.lg cs.ro denoising prediction trajectory type vision