3 accepted papers
Classical autonomous driving systems connect perception and prediction modules via hand-crafted bounding-box interfaces, limiting information flow and propagating errors to downstream tasks. Recent research aims to develop end-to-end models that jointly address perception and prediction; however, th…
"3D object detection is one of the most important components in any Self-Driving stack, but current object detectors require costly & slow manual annotation of 3D bounding boxes to perform well. Recently, several methods emerged to generate without human supervision, however, all of these methods ha…
Recently, several frameworks for self-supervised learning of 3D scene flow on point clouds have emerged. Scene flow inherently separates every scene into multiple moving agents and a large class of points following a single rigid sensor motion. However, existing methods do not leverage this property…