Indoor Scene Generation from a Collection of Semantic-Segmented Depth Images

1 code implementation • ICCV 2021 • Ming-Jia Yang, Yu-Xiao Guo, Bin Zhou, Xin Tong

Different from existing methods that represent an indoor scene with the type, location, and other properties of objects in the room and learn the scene layout from a collection of complete 3D indoor scenes, our method models each indoor scene as a 3D semantic scene volume and learns a volumetric generative adversarial network (GAN) from a collection of 2. 5D partial observations of 3D scenes.

Generative Adversarial Network Scene Generation