5 citations · 10 across the 3 of their papers we have counts for
3 papers
cs.CV2023★ 1 cited
PanopticNeRF-360: Panoramic 3D-to-2D Label Transfer in Urban Scenes
Xiao Fu, Shangzhan Zhang, Tianrun Chen +4
Training perception systems for self-driving cars requires substantial 2D annotations that are labor-intensive to manual label. While existing datasets provide rich annotations on…
cs.CV2023★ 5 cited
OmniObject3D: Large-Vocabulary 3D Object Dataset for Realistic Perception, Reconstruction and Generation
Tong Wu, Jiarui Zhang, Xiao Fu +9
Recent advances in modeling 3D objects mostly rely on synthetic datasets due to the lack of large-scale realscanned 3D databases. To facilitate the development of 3D perception, re…
cs.CV2022★ 4 cited
Panoptic NeRF: 3D-to-2D Label Transfer for Panoptic Urban Scene Segmentation
Xiao Fu, Shangzhan Zhang, Tianrun Chen +5
Large-scale training data with high-quality annotations is critical for training semantic and instance segmentation models. Unfortunately, pixel-wise annotation is labor-intensive…