用压缩纹理+元数据在解码端实现高质量3D视频，省带宽还防闪烁
A Single Atlas is All You Need: Decoder-Side Gaussian Splatting for Immersive Video
- 解码端直接用3D高斯点云生成视角，不传深度图
- 仅1张2D贴图+4个输入视图，画质提升5.79dB
- 压缩本身起平滑作用，减少视差抖动
沉浸式视频传输受像素率限制，高分辨率深度图或显式三维体数据传输成本高昂。解码端深度估计（DSDE）将深度计算移至客户端，但在复杂几何、视间闪烁和非朗伯反射场景下表现不佳。3D高斯溅射（3DGS）虽具顶级视图合成能力，但传输点云或其投影2D图谱的带宽开销巨大，且与标准视频编码器不兼容。本文提出解码端高斯溅射（DSGS），将DSDE中的深度估计阶段替换为前馈3DGS推理，完全在解码端基于压缩纹理和元数据优化体积场景。核心发现是：有损压缩相当于隐式低通滤波器，稳定前馈点云预测——压缩比特流质量超过无损，同时体积缩小十倍。在极端视图稀疏条件下（1张2D贴图含4个输入视图），相比DSDE基线，DSGS实现+5.79 dB BD-PSNR与+0.054 BD-SSIM增益，最大视间Delta IV-PSNR从17.2 dB降至6.4 dB，显著缩小传输与虚拟视口间的域偏移。
原文摘要 · Abstract (English)
Immersive video delivery is bottlenecked by pixel-rate constraints, making the transmission of high-resolution depth maps or explicit 3D volumetric data expensive. Decoder-Side Depth Estimation (DSDE) shifts depth computation to the client, but struggles with complex geometries, inter-view flickering, and non-Lambertian reflections. Conversely, 3D Gaussian Splatting (3DGS) offers state-of-the-art view synthesis, but transmitting splats (or their projected 2D maps) incurs prohibitive bandwidth costs and is poorly aligned with standard video codecs. We propose Decoder-Side Gaussian Splatting (DSGS), a framework that natively replaces the depth-estimation stage of DSDE with feed-forward 3DGS inference, optimizing volumetric scenes entirely on the decoder side from compressed textures and metadata. A central, counterintuitive finding is that lossy compression acts as an implicit low-pass filter stabilizing feed-forward splat prediction: compressed bitstreams exceed lossless quality while shrinking tenfold. Under extreme view sparsity (one 2D atlas comprising 4 input views), DSGS achieves a +5.79 dB BD-PSNR and +0.054 BD-SSIM gain over the DSDE anchor while reducing maximum inter-view Delta IV-PSNR from 17.2 dB to 6.4 dB, minimizing the domain shift between transmitted and virtual viewports.
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