MONOCULAR 3D OBJECT LOCALIZATION FROM TEMPORAL AGGREGATION

摘要

A method provided for 3D object localization predicts (610) pairs of 2D bounding boxes. Each pair corresponds to a detected object in each of the two consecutive input monocular images. The method generates (620), for each detected object, a relative motion estimation specifying a relative motion between the two images. The method constructs (630) an object cost volume by aggregating temporal features from the two images using the pairs of 2D bounding boxes and the relative motion estimation to predict a range of object depth candidates and a confidence score for each object depth candidate and an object depth from the object depth candidates. The method updates (640) the relative motion estimation based on the object cost volume and the object depth to provide a refined object motion and a refined object depth. The method reconstructs (650) a 3D bounding box for each detected object based on the refined object motion and refined object depth.