Capacity-Controlled Multi-View Stylization of 3D Gaussian Splatting

摘要

While 3D Gaussian Splatting (3DGS) provides an efficientand explicit representation for novel view synthesis, enforcing stylisticcoherence across viewpoints remains challenging. Existing 3D stylizationmethods typically apply 2D feature-matching losses independently perrendered view, which leads to unstable style allocation, many-to-one fea-ture reuse, and limited cross-view consistency. We propose a capacity-controlled framework for multi-view stylization of 3DGS, grounded inoptimal transport. Specifically, we reformulate local style matching as asemi-balanced optimal transport problem. By introducing explicit column-capacity constraints with tunable strength, our formulation mitigatesmany-to-one matching and enables controllable allocation of style fea-tures. This transport-based objective provides a principled mechanismfor balancing feature coverage and stylistic diversity while maintainingstable correspondences across viewpoints. To further enhance cross-viewcoherence, we incorporate a novel cross-view matching guidance to con-strain correspondences between scene content and style patterns. In ad-dition, we introduce several geometric regularizations to enhance thevanilla 3DGS, thereby enabling optimized Gaussian primitives to rep-resent finer-grained textures during stylization. Extensive experimentsdemonstrate that our approach significantly improves multi-view stylis-tic consistency and produces stable, expressive 3D stylizations while pre-serving the core semantic structure of the scene.