English(EN) BoundedGS: Memory-Efficient High-Resolution Training for 3D Gaussian Splatting

BoundedGS 降低了高分辨率3D高斯溅射训练的内存使用量

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-27 04:00

研究人员开发了BoundedGS，一种用于训练高分辨率3D高斯溅射模型的新颖方法，可显著降低内存使用量。该技术通过分离光栅化和投影后向传播以及限制活动局部光栅化工作集来优化内存。BoundedGS 在内存消耗方面实现了大幅降低，同时保持了重建质量，甚至缩短了高分辨率场景的训练时间。 AI

影响降低了高分辨率3D场景生成所需的内存，可能使更广泛的技术得到采用。

排序理由该集群包含一篇详细介绍3D高斯溅射新方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]

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本文如何被排名

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Newsworthiness bucket: Tool; 该集群包含一篇详细介绍3D高斯溅射新方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]
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arXiv cs.CV TIER_1 English(EN) · Xiaobin Deng, Changyu Diao, Min Li, Duanqing Xu · 2026-10-27 04:00

BoundedGS：3D高斯泼溅的高内存效率高分辨率训练

arXiv:2610.34233v1 Announce Type: new Abstract: High-resolution 3D Gaussian Splatting training increases pixel and Gaussian-tile intersection counts, expanding rasterization caches that coexist with projection and gradient state at peak memory. A complete-view update aggregates g…