most citedGenerative Diffusion Prior for Unified Image Restoration and Enhancement

10 citations · 14 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20241 cited

RefGaussian: Disentangling Reflections from 3D Gaussian Splatting for Realistic Rendering

Rui Zhang, Tianyue Luo, Weidong Yang +5

3D Gaussian Splatting (3D-GS) has made a notable advancement in the field of neural rendering, 3D scene reconstruction, and novel view synthesis. Nevertheless, 3D-GS encounters the…

cs.MM2024

Towards Unified Representation of Multi-Modal Pre-training for 3D Understanding via Differentiable Rendering

Ben Fei, Yixuan Li, Weidong Yang +2

State-of-the-art 3D models, which excel in recognition tasks, typically depend on large-scale datasets and well-defined category sets. Recent advances in multi-modal pre-training h…

cs.CV20241 cited

GetMesh: A Controllable Model for High-quality Mesh Generation and Manipulation

Zhaoyang Lyu, Ben Fei, Jinyi Wang +4

Mesh is a fundamental representation of 3D assets in various industrial applications, and is widely supported by professional softwares. However, due to its irregular structure, me…

cs.CV20242 cited

Visual Foundation Models Boost Cross-Modal Unsupervised Domain Adaptation for 3D Semantic Segmentation

Jingyi Xu, Weidong Yang, Lingdong Kong +4

Unsupervised domain adaptation (UDA) is vital for alleviating the workload of labeling 3D point cloud data and mitigating the absence of labels when facing a newly defined domain.…

cs.CV202310 cited

Generative Diffusion Prior for Unified Image Restoration and Enhancement

Ben Fei, Zhaoyang Lyu, Liang Pan +5

Existing image restoration methods mostly leverage the posterior distribution of natural images. However, they often assume known degradation and also require supervised training,…