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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

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Showing 2025 · cs.CVShow all

5 papers · 2 filters

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…