2D-3D-S

2D-3D-Semantic

The 2D-3D-S dataset provides a variety of mutually registered modalities from 2D, 2.5D and 3D domains, with instance-level semantic and geometric annotations. It covers over 6,000 m2 collected in 6 large-scale indoor areas that originate from 3 different buildings. It contains over 70,000 RGB images, along with the corresponding depths, surface normals, semantic annotations, global XYZ images (all in forms of both regular and 360° equirectangular images) as well as camera information. It also includes registered raw and semantically annotated 3D meshes and point clouds. The dataset enables development of joint and cross-modal learning models and potentially unsupervised approaches utilizing the regularities present in large-scale indoor spaces. Source: https://github.com/alexsax/2D-3D-Semantics Image Source: https://github.com/alexsax/2D-3D-Semantics

Images

벤치마크

Semantic Segmentation on Stanford2D3D Panoramic 결과 50개

3D Room Layouts From A Single RGB Panorama on Stanford2D3D Panoramic 결과 45개

Depth Estimation on Stanford2D3D Panoramic 결과 36개

Semantic Segmentation on Stanford2D3D - RGBD 결과 12개

Semantic Segmentation on Stanford2D3D Panoramic - RGBD 결과 6개

Semi-Supervised Semantic Segmentation on 2D-3D-S 결과 2개