CVPR 2023 – MACARONS: Mapping And Coverage Anticipation with RGB Online Self-Supervision

In this episode we discuss MACARONS: Mapping And Coverage Anticipation with RGB Online Self-Supervision
by Antoine Guédon, Tom Monnier, Pascal Monasse, Vincent Lepetit. The paper introduces a method that can learn to explore and reconstruct large environments in 3D from color images only, without relying on depth sensors or 3D supervision. The method learns to predict a “volume occupancy field” from color images and uses it to identify the Next Best View (NBV) to improve scene coverage. As a result, the method performs well on new scenes and outperforms recent methods that require depth sensors, making it a more realistic option for outdoor scenes captured with a drone.