With the recent advances in AR/VR recently a wider range of applications such as virtual touring, Building Information Modeling (BIM), e.g. floorplan generation and 3D holistic understanding have been emerging. Such applications have attracted a lot of interest from both academia and industry and motivated a lot of investments in the form of dataset collection, research, publications and products. A few recent examples of such datasets are Zillow Indoor Dataset (ZInD), Apple’s ARKit Scenes dataset and Facebook’s Habitat-Matterport dataset. The size and unique type of annotations provided by each of these datasets provide a huge opportunity for CV/ML researchers to focus on different aspects of scene and environment understanding beyond what was possible before.

Motivated by the recent release of datasets such as Zillow Indoor Dataset (ZInD), Apple's ARKit Scenes dataset and Facebook's Habitat-Matterport dataset, in this workshop we would like to bring industry and academia together and encourage both to focus on specific under explored aspects of environment understanding. We encourage researchers to go beyond "scene understanding" and explore "environment understanding" with a focus on understanding structure through tasks such as 2D/3D room layout estimation, understanding relation of "rooms" for floorplan generation, localization of media within rooms and floorplans, localization of objects within rooms and floorplans. Image, geometric, and semantic information can also be used to reimagine the appearance of home interiors in a photorealistic manner.