Xiuzhe Wu

ORCID: 0000-0002-5565-4541
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About
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Research Areas
  • 3D Shape Modeling and Analysis
  • 3D Surveying and Cultural Heritage
  • Optical measurement and interference techniques
  • Advanced Optical Sensing Technologies
  • Advanced Memory and Neural Computing
  • CCD and CMOS Imaging Sensors

University of Hong Kong
2024

In this paper, we present an implicit surface reconstruction method with 3D Gaussian Splatting (3DGS), namely 3DGSR, that allows for accurate intricate details while inheriting the high efficiency and rendering quality of 3DGS. The key insight is to incorporate signed distance field (SDF) within Gaussians modeling, enable alignment joint optimization both SDF Gaussians. To achieve this, design coupling strategies align associate Gaussians, allowing unified enforcing constraints on With...

10.1145/3687952 article EN ACM Transactions on Graphics 2024-11-19

In this paper, we present an implicit surface reconstruction method with 3D Gaussian Splatting (3DGS), namely 3DGSR, that allows for accurate intricate details while inheriting the high efficiency and rendering quality of 3DGS. The key insight is incorporating signed distance field (SDF) within Gaussians to enable them be aligned jointly optimized. First, introduce a differentiable SDF-to-opacity transformation function converts SDF values into corresponding Gaussians' opacities. This...

10.48550/arxiv.2404.00409 preprint EN arXiv (Cornell University) 2024-03-30

Human beings construct perception of space by integrating sparse observations into massively interconnected synapses and neurons, offering a superior parallelism efficiency. Replicating this capability in AI finds wide applications medical imaging, AR/VR, embodied AI, where input data is often computing resources are limited. However, traditional signal reconstruction methods on digital computers face both software hardware challenges. On the front, difficulties arise from storage...

10.48550/arxiv.2404.09613 preprint EN arXiv (Cornell University) 2024-04-15
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