  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.

Computer Vision and Pattern Recognition