Mesh-Aligned 3D Gaussian Splatting for Multi-Resolution Anti-Aliasing Rendering

作者：Jiaming Liu, Linghe Kong, Jiajie Yan, Guihai Chen · 发表于：IEEE Transactions on Circuits and Systems for Video Technology · 年份：2025 · DOI：10.1109/tcsvt.2025.3544760 · 被引用次数：9 · 研究领域：Computer Graphics and Visualization Techniques、3D Shape Modeling and Analysis、Video Surveillance and Tracking Methods

3D Gaussian splatting (3DGS) suggests the use of explicit point-based 3D representations for high-fidelity novel view synthesis, with training and rendering speeds that are better than prior neural radiance fields. However, 3DGS relies heavily on synthetic point clouds generated by structure from motion (SfM) or multi view stereo (MVS) techniques, and lacks a well-defined method to initially condition them. In this work, we first propose a mesh-aligned method that attaches the 3D Gaussian to the extracted surface meshes for reliable initialization during training, and then directly manipulates the learnable 3DGS in the local coordinate using the triangular meshes. In addition, to constrain the stereo Gaussian on a planar mesh for better rendering, both normal and depth losses are designed to optimize the orientation and significance of the Gaussian. In practice, we further apply this method to multi-resolution scene rendering while resolving the aliasing effect. Unlike directly changing the size and number of Gaussians that may interfere the rendering quality at different resolutions, we argue that the properties of the modelled mesh are naturally resistant to aliasing effects. By utilising triangular meshes for Gaussian binding and adaptive learning, the proposed method can maintain high-fidelity rendering after splatting on multi-resolution concrete images. Extensive experiments demonstrate the effectiveness of our approach and its advantages over single full-resolution bas...