分离时空特征，343帧/秒实时渲染高分辨率动态场景
Disentangled 4D Gaussian Splatting: Rendering High-Resolution Dynamic World at 343 FPS
- 分离时空维度，避免4D矩阵计算，减少冗余运算
- 1352×1014分辨率下达343帧/秒，存储节省超4.5%
- 适合需要实时动态渲染的虚拟现实与机器人应用
尽管从2D视频进行动态新视角合成已取得进展，但实现高效重建与渲染仍具挑战。本文提出解耦4D高斯点云（Disentangled4DGS），一种新型表示与渲染管道，在不损失视觉保真度的前提下实现实时性能。该方法将4D高斯的时空成分解耦，避免了先前方法中需先切片及进行四维矩阵计算的问题。通过将时空形变投影至动态2D高斯，并延迟时间处理，有效减少4DGS的冗余计算。同时引入梯度引导的光流损失和时间分割策略以降低伪影。实验表明，该方法在单张RTX3090上渲染1352×1014分辨率图像时达到343帧/秒，存储需求降低至少4.5%，在多视角与单视角动态场景数据集上均超越现有方法，树立了动态新视角合成的新基准。
原文摘要 · Abstract (English)
While dynamic novel view synthesis from 2D videos has seen progress, achieving efficient reconstruction and rendering of dynamic scenes remains a challenging task. In this paper, we introduce Disentangled 4D Gaussian Splatting (Disentangled4DGS), a novel representation and rendering pipeline that achieves real-time performance without compromising visual fidelity. Disentangled4DGS decouples the temporal and spatial components of 4D Gaussians, avoiding the need for slicing first and four-dimensional matrix calculations in prior methods. By projecting temporal and spatial deformations into dynamic 2D Gaussians and deferring temporal processing, we minimize redundant computations of 4DGS. Our approach also features a gradient-guided flow loss and temporal splitting strategy to reduce artifacts. Experiments demonstrate a significant improvement in rendering speed and quality, achieving 343 FPS when render 1352*1014 resolution images on a single RTX3090 while reducing storage requirements by at least 4.5%. Our approach sets a new benchmark for dynamic novel view synthesis, outperforming existing methods on both multi-view and monocular dynamic scene datasets.
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