3D-FUTURE: 3D Furniture shape with TextURE

Abstract

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.

Project Page: https://tianchi.aliyun.com/specials/promotion/alibaba-3d-future

References in corpus (7)

• MeshCNN: A Network with an Edge
• Matterport3D: Learning from RGB-D Data in Indoor Environments
• Semantic Instance Segmentation via Deep Metric Learning
• PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes
• InteriorNet: Mega-scale Multi-sensor Photo-realistic Indoor Scenes Dataset
• Im2Avatar: Colorful 3D Reconstruction from a Single Image
• Structured3D: A Large Photo-realistic Dataset for Structured 3D Modeling

Cited by in corpus (10)

• ATISS: Autoregressive Transformers for Indoor Scene Synthesis
• 3D-FRONT: 3D Furnished Rooms with layOuts and semaNTics
• OpenRooms: An End-to-End Open Framework for Photorealistic Indoor Scene Datasets
• TM-NET: Deep Generative Networks for Textured Meshes
• Panoptic 3D Scene Reconstruction From a Single RGB Image
• Towards Panoptic 3D Parsing for Single Image in the Wild
• Geometry-Based Layout Generation with Hyper-Relations AMONG Objects
• Hard Example Generation by Texture Synthesis for Cross-domain Shape Similarity Learning
• 2nd Place Solution to Instance Segmentation of IJCAI 3D AI Challenge 2020
• MINERVAS: Massive INterior EnviRonments VirtuAl Synthesis