activity
20222026
most citedComprehensive Review of Deep Learning-Based 3D Point Cloud Completion Processing and Analysis

215 citations · 460 across the 46 of their papers we have counts for

collaborators
Showing 2024 · cs.CVShow all

10 papers · 2 filters

cs.CV2024★ 1 cited

MBPU: A Plug-and-Play State Space Model for Point Cloud Upsamping with Fast Point Rendering

Jiayi Song, Weidong Yang, Zhijun Li +2

The task of point cloud upsampling (PCU) is to generate dense and uniform point clouds from sparse input captured by 3D sensors like LiDAR, holding potential applications in real y…

cs.CV2024

PostCast: Generalizable Postprocessing for Precipitation Nowcasting via Unsupervised Blurriness Modeling

Junchao Gong, Siwei Tu, Weidong Yang +6

Precipitation nowcasting plays a pivotal role in socioeconomic sectors, especially in severe convective weather warnings. Although notable progress has been achieved by approaches…

cs.CV2024

GS-PT: Exploiting 3D Gaussian Splatting for Comprehensive Point Cloud Understanding via Self-supervised Learning

Keyi Liu, Yeqi Luo, Weidong Yang +4

Self-supervised learning of point cloud aims to leverage unlabeled 3D data to learn meaningful representations without reliance on manual annotations. However, current approaches f…

cs.CV2024★ 1 cited

Taming Generative Diffusion Prior for Universal Blind Image Restoration

Siwei Tu, Weidong Yang, Ben Fei

Diffusion models have been widely utilized for image restoration. However, previous blind image restoration methods still need to assume the type of degradation model while leaving…

cs.CV2024★ 1 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.CV2024

3DMambaComplete: Exploring Structured State Space Model for Point Cloud Completion

Yixuan Li, Weidong Yang, Ben Fei

Point cloud completion aims to generate a complete and high-fidelity point cloud from an initially incomplete and low-quality input. A prevalent strategy involves leveraging Transf…

cs.CV2024★ 1 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.CV2024★ 2 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.CV2024★ 178 cited

3D Gaussian as a New Era: A Survey

Ben Fei, Jingyi Xu, Rui Zhang +3

3D Gaussian Splatting (3D-GS) has emerged as a significant advancement in the field of Computer Graphics, offering explicit scene representation and novel view synthesis without th…

cs.CV2024★ 2 cited

Topology-Aware Latent Diffusion for 3D Shape Generation

Jiangbei Hu, Ben Fei, Baixin Xu +6

We introduce a new generative model that combines latent diffusion with persistent homology to create 3D shapes with high diversity, with a special emphasis on their topological ch…