3D Object Visibility Prediction in Autonomous Driving

arXiv:2403.03681v1 Announce Type: cross
Abstract: With the rapid advancement of hardware and software technologies, research in autonomous driving has seen significant growth. The prevailing framework for multi-sensor autonomous driving encompasses sensor installation, perception, path planning, decision-making, and motion control. At the perception phase, a common approach involves utilizing neural networks to infer 3D bounding box (Bbox) attributes from raw sensor data, including classification, size, and orientation. In this paper, we present a novel attribute and its corresponding algorithm: 3D object …

3d object abstract advancement arxiv autonomous autonomous driving control cs.cv cs.ro decision driving framework growth hardware installation making networks neural networks object path perception planning prediction research sensor software technologies type visibility