215 citations · 460 across the 46 of their papers we have counts for
23 papers · 1 filter
Denoising-GS: Gaussian Splatting with Spatial-aware Denoising
Qingyuan Zhou, Xinyi Liu, Weidong Yang +5
Recent advances in 3D Gaussian Splatting (3DGS) have achieved remarkable success in high-fidelity Novel View Synthesis (NVS), yet the optimization process inevitably introduces noi…
OmniLiDAR: A Unified Diffusion Framework for Multi-Domain 3D LiDAR Generation
Youquan Liu, Weidong Yang, Ao Liang +9
LiDAR scene generation is increasingly important for scalable simulation and synthetic data creation, especially under diverse sensing conditions that are costly to capture at scal…
Earth-o1: A Grid-free Observation-native Atmospheric World Model
Junchao Gong, Kaiyi Xu, Wangxu Wei +22
Despite the unprecedented volume of multimodal data provided by modern Earth observation systems, our ability to model atmospheric dynamics remains constrained. Traditional modelin…
Multi-modal Multi-task Pre-training for Improved Point Cloud Understanding
Liwen Liu, Weidong Yang, Lipeng Ma +1
Recent advances in multi-modal pre-training methods have shown promising effectiveness in learning 3D representations by aligning multi-modal features between 3D shapes and their c…
A Multi-View High-Resolution Foot-Ankle Complex Point Cloud Dataset During Gait for Occlusion-Robust 3D Completion
Jie-Wen Li, Zi-Han Ye, Qingyuan Zhou +4
The kinematics analysis of foot-ankle complex during gait is essential for advancing biomechanical research and clinical assessment. Collecting accurate surface geometry data from…
Reflections Unlock: Geometry-Aware Reflection Disentanglement in 3D Gaussian Splatting for Photorealistic Scenes Rendering
Jiayi Song, Zihan Ye, Qingyuan Zhou +5
Accurately rendering scenes with reflective surfaces remains a significant challenge in novel view synthesis, as existing methods like Neural Radiance Fields (NeRF) and 3D Gaussian…
Gaussian2Scene: 3D Scene Representation Learning via Self-supervised Learning with 3D Gaussian Splatting
Keyi Liu, Weidong Yang, Ben Fei +1
Self-supervised learning (SSL) for point cloud pre-training has become a cornerstone for many 3D vision tasks, enabling effective learning from large-scale unannotated data. At the…
MGSR: 2D/3D Mutual-boosted Gaussian Splatting for High-fidelity Surface Reconstruction under Various Light Conditions
Qingyuan Zhou, Yuehu Gong, Weidong Yang +6
Novel view synthesis (NVS) and surface reconstruction (SR) are essential tasks in 3D Gaussian Splatting (3D-GS). Despite recent progress, these tasks are often addressed independen…
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…
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…
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…
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…
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…
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…
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…
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.…
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…
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…
DiffBIR: Towards Blind Image Restoration with Generative Diffusion Prior
Xinqi Lin, Jingwen He, Ziyan Chen +6
We present DiffBIR, a general restoration pipeline that could handle different blind image restoration tasks in a unified framework. DiffBIR decouples blind image restoration probl…
Self-supervised Learning for Pre-Training 3D Point Clouds: A Survey
Ben Fei, Weidong Yang, Liwen Liu +4
Point cloud data has been extensively studied due to its compact form and flexibility in representing complex 3D structures. The ability of point cloud data to accurately capture a…
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,…
UniDA3D: Unified Domain Adaptive 3D Semantic Segmentation Pipeline
Ben Fei, Siyuan Huang, Jiakang Yuan +5
State-of-the-art 3D semantic segmentation models are trained on off-the-shelf public benchmarks, but they will inevitably face the challenge of recognition accuracy drop when these…
Comprehensive Review of Deep Learning-Based 3D Point Cloud Completion Processing and Analysis
Ben Fei, Weidong Yang, Wenming Chen +5
Point cloud completion is a generation and estimation issue derived from the partial point clouds, which plays a vital role in the applications in 3D computer vision. The progress…