3D-FRONT: 3D Furnished Rooms with layOuts and semaNTics
This dataset provides a large-scale, high-quality resource for researchers working on 3D scene understanding, synthesis, and related computer vision tasks, addressing the need for diverse and well-structured indoor scene data.
This paper introduces 3D-FRONT, a new dataset of 18,968 synthetic indoor scenes with professional layouts and 13,151 high-quality textured 3D furniture objects. The dataset aims to provide style-consistent interior designs curated using a recommender system.
We introduce 3D-FRONT (3D Furnished Rooms with layOuts and semaNTics), a new, large-scale, and comprehensive repository of synthetic indoor scenes highlighted by professionally designed layouts and a large number of rooms populated by high-quality textured 3D models with style compatibility. From layout semantics down to texture details of individual objects, our dataset is freely available to the academic community and beyond. Currently, 3D-FRONT contains 18,968 rooms diversely furnished by 3D objects, far surpassing all publicly available scene datasets. In addition, the 13,151 furniture objects all come with high-quality textures. While the floorplans and layout designs are directly sourced from professional creations, the interior designs in terms of furniture styles, color, and textures have been carefully curated based on a recommender system we develop to attain consistent styles as expert designs. Furthermore, we release Trescope, a light-weight rendering tool, to support benchmark rendering of 2D images and annotations from 3D-FRONT. We demonstrate two applications, interior scene synthesis and texture synthesis, that are especially tailored to the strengths of our new dataset. The project page is at: https://tianchi.aliyun.com/specials/promotion/alibaba-3d-scene-dataset.