SIEVE: Topology-Flexible Mesh Compression via Surface-Intersection Coding

Existing implicit representation-based 3D mesh compression methods typically adopt signed distance fields representation, which can struggle to preserve open boundaries and thin structures. In this paper, we present SIEVE, Surface Intersection Encoding via Voxel Edges, a 3D mesh compression framework that encodes local surface intersections to accommodate diverse surface geometries and topologies. Its compact Dual Vertex–Edge (DV-Edge) representation stores grid-edge intersection flags and precomputed dual vertex positions on a sparse regular grid, encoding local geometry and the information needed to construct mesh connectivity. A hierarchical autoencoder compresses DV-Edge into an entropy-coded bitstream for mesh reconstruction. Extensive experiments on challenging scanned meshes and geometrically irregular surfaces demonstrate improved rate–distortion performance over the evaluated baselines, with better preservation of fine surface structures. The code will be publicly available.