报告主题：用于动态场景实时渲染的4D Gaussian Splatting算法报告日期：2月22日（周四）14:30-15:30
主题简介：建模与渲染动态场景一直是一个重要且具有挑战性的任务，对于高效率建模复杂的运动尤为如此。为了达成实时渲染动态场景并同时保证高训练与存储效率的目标，我们提出了4D高斯溅射（4D-GS）作为一种全面的动态场景表达方式，而不是对每个单独的帧应用3D-GS。在4D-GS中，我们提出了一种包含3D高斯和4D神经体素的新型显式表达。我们提出了一种受HexPlane启发的分解神经体素编码算法，以高效地从4D神经体素构建高斯特征，然后应用轻量级MLP来预测新时间戳的高斯形变。我们的4D-GS方法实现了高分辨率下的实时渲染，在RTX 3090 GPU上以800×800分辨率达到82 FPS，同时保持与以往最先进方法相当或更好的质量。更多的可视化结果和代码详见: guanjunwu.github.io/4dgs报告嘉宾：吴官骏，华中科技大学计算机学院博士研究生在读，博士生导师为王兴刚教授。主要研究方向为神经渲染与三维重建。近期工作4D Gaussian Splatting for Real-Time Dynamic Scene Rendering 在github获得Stars 1300+，谷歌学术引用50余次。个人主页：guanjunwu.github.io扫描下方二维码
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