CVPR 2023 - OmniObject3D: Large-Vocabulary 3D Object Dataset for

In this episode we discuss OmniObject3D: Large-Vocabulary 3D Object Dataset for by Tong Wu, Jiarui Zhang, Xiao Fu, Yuxin Wang, Jiawei Ren, Liang Pan, Wayne Wu, Lei Yang, Jiaqi Wang, Chen Qian, Dahua Lin, Ziwei Liu. The paper proposes OmniObject3D, a large vocabulary 3D object dataset containing 6,000 high-quality real-scanned objects in 190 daily categories with rich annotations. The dataset aims to facilitate the development of 3D perception, reconstruction, and generation in the real world and is evaluated on four benchmarks: robust 3D perception, novel-view synthesis, neural surface reconstruction, and 3D object generation. The extensive studies on these benchmarks reveal new observations, challenges, and opportunities for future research in realistic 3D vision.