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20232026
most citedCrossGen: Learning and Generating Cross Fields for Quad Meshing

3 citations · 7 across the 19 of their papers we have counts for

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7 papers · 1 filter

cs.CV2024

SVGS: Enhancing Gaussian Splatting Using Primitives with Spatially Varying Colors

Rui Xu, Wenyue Chen, Jiepeng Wang +7

Gaussian Splatting demonstrates impressive results in multi-view reconstruction based on Gaussian explicit representations. However, the current Gaussian primitives only have a sin…

cs.CV2024

NASM: Neural Anisotropic Surface Meshing

Hongbo Li, Haikuan Zhu, Sikai Zhong +7

This paper introduces a new learning-based method, NASM, for anisotropic surface meshing. Our key idea is to propose a graph neural network to embed an input mesh into a high-dimen…

cs.CV2024

Deep-PE: A Learning-Based Pose Evaluator for Point Cloud Registration

Junjie Gao, Chongjian Wang, Zhongjun Ding +4

In the realm of point cloud registration, the most prevalent pose evaluation approaches are statistics-based, identifying the optimal transformation by maximizing the number of con…

cs.CV2024

NeurCross: A Neural Approach to Computing Cross Fields for Quad Mesh Generation

Qiujie Dong, Huibiao Wen, Rui Xu +6

Quadrilateral mesh generation plays a crucial role in numerical simulations within Computer-Aided Design and Engineering (CAD/E). Producing high-quality quadrangulation typically r…

cs.CV2024

NeurCADRecon: Neural Representation for Reconstructing CAD Surfaces by Enforcing Zero Gaussian Curvature

Qiujie Dong, Rui Xu, Pengfei Wang +5

Despite recent advances in reconstructing an organic model with the neural signed distance function (SDF), the high-fidelity reconstruction of a CAD model directly from low-quality…

cs.CV2023

D3Former: Jointly Learning Repeatable Dense Detectors and Feature-enhanced Descriptors via Saliency-guided Transformer

Junjie Gao, Pengfei Wang, Qiujie Dong +3

Establishing accurate and representative matches is a crucial step in addressing the point cloud registration problem. A commonly employed approach involves detecting keypoints wit…

cs.CV2023

OAAFormer: Robust and Efficient Point Cloud Registration Through Overlapping-Aware Attention in Transformer

Junjie Gao, Qiujie Dong, Ruian Wang +4

In the domain of point cloud registration, the coarse-to-fine feature matching paradigm has received substantial attention owing to its impressive performance. This paradigm involv…