Chao Wang | Bytedance/TikTok
Description: Announcing the SUMO challenge - a contest to encourage the development of algorithms for comprehensive understanding of 3D indoor scenes from 360° RGB-D panoramas with the goal of enabling social AR and VR research and experiences.
The SUMO Challenge targets the development of algorithms for comprehensive understanding of 3D indoor scenes from 360° RGB-D panoramas . The target 3D models of indoor scenes include all visible layout elements and objects complete with pose , semantic information , and texture . Algorithms submitted are evaluated at 3 levels of complexity corresponding to 3 tracks of the challenge: oriented 3D bounding boxes , oriented 3D voxel grids , and oriented 3D meshes . SUMO Challenge results will be presented at th
The good news is that the 2019 SUMO Workshop will go on as planned. We have a great lineup of speakers, and we encourage you to submit papers related to 3D scene understanding and computer vision using 360 degree imagery. For more information, visit the workshop web site .
The SUMO challenge dataset is derived from processing scenes from the SUNCG dataset to produce 360° RGB-D images represented as cubemaps and corresponding 3D mesh models of all visible scene elements. The mesh models are further processed into a bounding box and voxel-based representation. The dataset format is described in detail in the SUMO white paper .
Chao Wang | Bytedance/TikTok