3D-FUTURE: 3D Furniture Shape with TextURE

被引:57
|
作者
Fu, Huan [1 ]
Jia, Rongfei [1 ]
Gao, Lin [2 ]
Gong, Mingming [3 ]
Zhao, Binqiang [1 ]
Maybank, Steve [4 ]
Tao, Dacheng [5 ]
机构
[1] Alibaba Grp, Tao Technol Dept, Hangzhou, Peoples R China
[2] Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China
[3] Univ Melbourne, Parkville, Vic, Australia
[4] Univ London, Birkbeck Coll, Dept Comp Sci & Informat Syst, London, England
[5] Univ Sydney, Sch Comp Sci, Camperdown, NSW, Australia
基金
澳大利亚研究理事会;
关键词
3D-FUTURE; Furniture shapes; Textures; Interior designs; Synthetic images; MEANS CLUSTERING-ALGORITHM; OBJECT; RECOGNITION; DATABASE;
D O I
10.1007/s11263-021-01534-z
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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 9992 modern 3D furniture shapes with high-resolution textures and detailed attributes. To support the studies of 3D modeling from images, we couple the CAD models with 20,240 scene images. The room scenes are designed by professional designers or generated by an industrial scene creating system. Given the well-organized 3D-FUTURE and its characteristics, we provide a package of baseline experiments, such as joint 2D instance segmentation and 3D object pose estimation, image-based 3D shape retrieval, 3D object reconstruction from a single image, texture recovery for 3D shapes, and furniture composition, to facilitate related future researches on our database.
引用
收藏
页码:3313 / 3337
页数:25
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