A Dataset for High-Level 3D Scene Understanding of Complex Road Scenes in the Top-View

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Publication Date: 6/17/2019

Event: Proceedings of CVPR 2019 Workshop on 3D Scene Understanding for Vision, Graphics, and Robotics

Reference: pp. 1-4, 2019

Authors: Ziyan Wang, Carnegie Mellon University, NEC Laboratories America, Inc.; Buyu Liu, NEC Laboratories America, Inc.; Samuel Schulter, NEC Laboratories America, Inc.; Manmohan Chandraker, NEC Laboratories America, Inc.

Abstract: We introduce a novel dataset for high-level 3D scene understanding of complex road scenes. Our annotations extend the existing datasets KITTI [5] and nuScenes [1] with semantically and geometrically meaningful attributes like the number of lanes or the existence of, and distance to, intersections, sidewalks and crosswalks. Our attributes are rich enough to build a meaningful representation of the scene in the top-view and provide a tangible interface to the real world for several practical applications

Publication Link: https://scene-understanding.com/2019/program.html