10 citations · 13 across the 11 of their papers we have counts for
11 papers
ScaleBlind: Point Cloud Completion under Unknown Scale
Shenghui Wu, Chen Wang, Yuan Feng +3
Point cloud completion aims to infer a complete 3D shape from a partial point cloud and serves as a fundamental building block for downstream tasks such as reconstruction, editing,…
UniRED: Unified RGB-D Video Frame Interpolation with Event Guidance
Yinuo Zhang, Guangshun Wei, Yuanfeng Zhou +1
High frame-rate RGB-D videos are crucial for a variety of downstream tasks, including motion analysis, dynamic scene understanding, and 3D reconstruction. However, due to hardware…
SAND: Spatially Adaptive Network Depth for Fast Sampling of Neural Implicit Surfaces
Chuanxiang Yang, Junhui Hou, Yuan Liu +5
Implicit neural representations are powerful for geometric modeling, but their practical use is often limited by the high computational cost of network evaluations. We observe that…
TSegAgent: Zero-Shot Tooth Segmentation via Geometry-Aware Vision-Language Agents
Shaojie Zhuang, Lu Yin, Guangshun Wei +3
Automatic tooth segmentation and identification from intra-oral scanned 3D models are fundamental problems in digital dentistry, yet most existing approaches rely on task-specific…
Detecting Dental Landmarks from Intraoral 3D Scans: the 3DTeethLand challenge
Achraf Ben-Hamadou, Nour Neifar, Ahmed Rekik +23
Teeth landmark detection is a key task in modern orthodontics, supporting advanced diagnosis, personalized treatment planning, and effective monitoring of treatment progress. Howev…
T-MLP: Tailed Multi-Layer Perceptron for Level-of-Detail Signal Representation
Chuanxiang Yang, Yuanfeng Zhou, Guangshun Wei +4
Level-of-detail (LoD) representation is critical for efficiently modeling and transmitting various types of signals, such as images and 3D shapes. In this work, we propose a novel…
PCDreamer: Point Cloud Completion Through Multi-view Diffusion Priors
Guangshun Wei, Yuan Feng, Long Ma +3
This paper presents PCDreamer, a novel method for point cloud completion. Traditional methods typically extract features from partial point clouds to predict missing regions, but t…
Monge-Ampere Regularization for Learning Arbitrary Shapes from Point Clouds
Chuanxiang Yang, Yuanfeng Zhou, Guangshun Wei +4
As commonly used implicit geometry representations, the signed distance function (SDF) is limited to modeling watertight shapes, while the unsigned distance function (UDF) is capab…
iPUNet:Iterative Cross Field Guided Point Cloud Upsampling
Guangshun Wei, Hao Pan, Shaojie Zhuang +2
Point clouds acquired by 3D scanning devices are often sparse, noisy, and non-uniform, causing a loss of geometric features. To facilitate the usability of point clouds in downstre…
3DTeethSeg'22: 3D Teeth Scan Segmentation and Labeling Challenge
Achraf Ben-Hamadou, Oussama Smaoui, Ahmed Rekik +29
Teeth localization, segmentation, and labeling from intra-oral 3D scans are essential tasks in modern dentistry to enhance dental diagnostics, treatment planning, and population-ba…
Dense Representative Tooth Landmark/axis Detection Network on 3D Model
Guangshun Wei, Zhiming Cui, Jie Zhu +5
Artificial intelligence (AI) technology is increasingly used for digital orthodontics, but one of the challenges is to automatically and accurately detect tooth landmarks and axes.…