With the rapid development of data-driven techniques, data has played an essential role in various computer vision tasks. Many realistic and synthetic datasets have been proposed to address different problems. However, there are lots of unresolved challenges: (1) the creation of dataset is usually a tedious process with manual annotations, (2) most datasets are only designed for a single specific task, (3) the modification or randomization of the 3D scene is difficult, and (4) the release of commercial 3D data may encounter copyright issue. This paper presents MINERVAS, a Massive INterior EnviRonments VirtuAl Synthesis system, to facilitate the 3D scene modification and the 2D image synthesis for various vision tasks. In particular, we design a programmable pipeline with Domain-Specific Language, allowing users to (1) select scenes from the commercial indoor scene database, (2) synthesize scenes for different tasks with customized rules, and (3) render various imagery data, such as visual color, geometric structures, semantic label. Our system eases the difficulty of customizing massive numbers of scenes for different tasks and relieves users from manipulating fine-grained scene configurations by providing user-controllable randomness using multi-level samplers. Most importantly, it empowers users to access commercial scene databases with millions of indoor scenes and protects the copyright of core data assets, e.g., 3D CAD models. We demonstrate the validity and flexibility of our system by using our synthesized data to improve the performance on different kinds of computer vision tasks.
翻译:随着数据驱动技术的迅速发展,数据在各种计算机愿景任务中发挥了不可或缺的作用,许多现实和合成的数据集被提出来应对不同的问题,然而,还存在许多尚未解决的挑战:(1) 数据集的创建通常是一个乏味的过程,带有手动说明;(2) 多数数据集仅设计为单一的具体任务;(3) 3D场景的修改或随机化十分困难;(4) 商业3D数据的发布可能会遇到版权问题。本文介绍了MINERSERVAS, 一个大规模Interire EnviRonments VirtuAl合成系统, 以便利3D场景的修改和2D图像合成。特别是,我们设计了一个可编程的管道,用Domain-Secifical语言,使用户能够选择室内商业场景数据库的场景,(2) 以定制规则对不同任务的综合场景进行修改或随机化,使不同任务场景的场景的场景数量更难以定制,我们系统在调控精细的场景中可以减轻用户的难度。