提出统一控制机制，让3D高斯点云在压缩与画质间自由切换。
ControlGS: Consistent Structural Compression Control for Deployment-Aware Gaussian Splatting
- 设计连续可调的控制轴，统一调节高斯点数量与画质
- 相同点数下画质显著优于现有方法，支持跨场景通用
- 无需针对不同场景调参，适合自动化部署于各类设备
3D高斯点云（3DGS）是一种高度可部署的实时新视角合成方法。实践中，需要一种通用且一致的控制机制，在不依赖场景特定调优的前提下，调节渲染质量与模型压缩之间的权衡，从而实现不同设备性能和通信带宽下的自动化部署。本文提出ControlGS，一种面向控制的优化框架，将高斯点数量与渲染质量的权衡映射到一条连续、场景无关且响应迅速的控制轴上。在多种场景尺度和类型（从小物体到大型户外场景）上的大量实验表明，通过调整全局统一的控制超参数，ControlGS能灵活生成偏向结构紧凑或高保真度的模型，不受具体场景规模或复杂度影响，且在相同或更少高斯点下实现显著更高的渲染质量，优于现有竞争方法。
原文摘要 · Abstract (English)
3D Gaussian Splatting (3DGS) is a highly deployable real-time method for novel view synthesis. In practice, it requires a universal, consistent control mechanism that adjusts the trade-off between rendering quality and model compression without scene-specific tuning, enabling automated deployment across different device performances and communication bandwidths. In this work, we present ControlGS, a control-oriented optimization framework that maps the trade-off between Gaussian count and rendering quality to a continuous, scene-agnostic, and highly responsive control axis. Extensive experiments across a wide range of scene scales and types (from small objects to large outdoor scenes) demonstrate that, by adjusting a globally unified control hyperparameter, ControlGS can flexibly generate models biased toward either structural compactness or high fidelity, regardless of the specific scene scale or complexity, while achieving markedly higher rendering quality with the same or fewer Gaussians compared to potential competing methods. Project page: https://zhang-fengdi.github.io/ControlGS/
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