S4R: Self-Supervised Semantic Scene Reconstruction from RGB-D Scans

Abstract

Figure 1. Given sparse RGB-D images, our method is capable of jointly predicting complete geometry, appearance, and semantic labels without access to any 3D or 2D in-place ground-truth annotations during training.