3D-FUTURE: 3D Furniture shape with TextURE
This dataset enables more comprehensive research in 3D vision tasks like reconstruction and texture recovery for the computer vision community, though it is incremental as it focuses on improving data quality rather than proposing new methods.
The paper introduces 3D-FUTURE, a large-scale dataset of 3D furniture shapes with high-resolution textures, containing 20,240 synthetic images and 9,992 detailed 3D instances, to address the lack of detailed and textured 3D models in existing benchmarks.
The 3D CAD shapes in current 3D benchmarks are mostly collected from online model repositories. Thus, they typically have insufficient geometric details and less informative textures, making them less attractive for comprehensive and subtle research in areas such as high-quality 3D mesh and texture recovery. This paper presents 3D Furniture shape with TextURE (3D-FUTURE): a richly-annotated and large-scale repository of 3D furniture shapes in the household scenario. At the time of this technical report, 3D-FUTURE contains 20,240 clean and realistic synthetic images of 5,000 different rooms. There are 9,992 unique detailed 3D instances of furniture with high-resolution textures. Experienced designers developed the room scenes, and the 3D CAD shapes in the scene are used for industrial production. Given the well-organized 3D-FUTURE, we provide baseline experiments on several widely studied tasks, such as joint 2D instance segmentation and 3D object pose estimation, image-based 3D shape retrieval, 3D object reconstruction from a single image, and texture recovery for 3D shapes, to facilitate related future researches on our database.