12 citations · 16 across the 12 of their papers we have counts for
5 papers · 1 filter
Text-Image Conditioned Diffusion for Consistent Text-to-3D Generation
Yuze He, Yushi Bai, Matthieu Lin +5
By lifting the pre-trained 2D diffusion models into Neural Radiance Fields (NeRFs), text-to-3D generation methods have made great progress. Many state-of-the-art approaches usually…
TBench: Benchmarking Current Progress in Text-to-3D Generation
Yuze He, Yushi Bai, Matthieu Lin +6
Recent methods in text-to-3D leverage powerful pretrained diffusion models to optimize NeRF. Notably, these methods are able to produce high-quality 3D scenes without training on 3…
MMPI: a Flexible Radiance Field Representation by Multiple Multi-plane Images Blending
Yuze He, Peng Wang, Yubin Hu +4
This paper presents a flexible representation of neural radiance fields based on multi-plane images (MPI), for high-quality view synthesis of complex scenes. MPI with Normalized De…
O-Recon: Completing 3D Reconstruction of Occluded Objects in the Scene with a Pre-trained 2D Diffusion Model
Yubin Hu, Sheng Ye, Wang Zhao +5
Occlusion is a common issue in 3D reconstruction from RGB-D videos, often blocking the complete reconstruction of objects and presenting an ongoing problem. In this paper, we propo…
Efficient Semantic Segmentation by Altering Resolutions for Compressed Videos
Yubin Hu, Yuze He, Yanghao Li +4
Video semantic segmentation (VSS) is a computationally expensive task due to the per-frame prediction for videos of high frame rates. In recent work, compact models or adaptive net…