Learning for Active 3D Mapping

Paper of authors K. Zimmermann, T. Petricek, V. Salansky, and T. Svoboda was accepted as oral presentation at ICCV 2017!

We propose an active 3D mapping method for depth sensors, which allow individual control of depth-measuring rays, such as the newly emerging solid-state lidars. The method simultaneously (i) learns to reconstruct a dense 3D occupancy map from sparse depth measurements, and (ii) optimizes the reactive control of depth-measuring rays.

Responsible person: Petr Pošík