Two Stream 3D Semantic Scene Completion

Understand

Inferring the 3D geometry and the semantic meaning of surfaces, which are occluded, is a very challenging task.

• Recently, a first end-to-end learning approach has been proposed that completes a scene from a single depth image.
• The approach voxelizes the scene and predicts for each voxel if it is occupied and, if it is occupied, the semantic class label.
• In this work, we propose a two stream approach that leverages depth information and semantic information, which is inferred from the RGB image, for this task.