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DCUDF2: Improving Efficiency and Accuracy in Extracting Zero Level Sets From Unsigned Distance Fields

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PRE
AI
X
X T Chen
F
F.X. Yu
F
Fei Hou
W
Wencheng Wang
Z
Zhebin Zhang
Y
Ying He
DOI：10.1109/TVCG.2025.3588659delete
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摘要

摘要

En 中文
无符号距离场（UDFs）为具有复杂拓扑结构的模型提供了灵活的表示方法，但准确提取其零水平集仍然具有挑战性，特别是在保持拓扑正确性和精细几何细节方面。我们提出了DCUDF2，这是一种基于DCUDF改进的方法，旨在解决这些局限性。我们的方法引入了一种具有自适应权重的精度感知损失函数，能够在实现精确几何拟合的同时避免过度平滑。为提高鲁棒性，我们提出了一种拓扑校正策略，以降低对超参数设置的敏感性。此外，我们开发了利用自适应权重的新操作，以加速收敛并提高运行效率。在多样化数据集上的大量实验表明，DCUDF2在几何保真度和拓扑精度两方面均持续优于DCUDF和现有方法。
Keyword:
Unsigned distance fields
mesh extraction
neural implicit fields
double covering

期刊

IEEE Transactions on Visualization and Computer Graphics 封面图
IEEE Transactions on Visualization and Computer Graphics
IF:
6.5
论文数:
353
被引数:
2.2W

机构

O
oppo research center
学者数:
1
论文数: 1
被引数: 0
I
Institute of Software
学者数:
90
论文数: 45
被引数: 571
N
Nanyang Technological University
学者数:
4.9W
论文数: 4.8W
被引数: 8.1W
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