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English(EN) ABCD: Alpha-Composited Block Coordinate Descent: Constant-VRAM Training for Large Radiance Fields

新的ABCD框架可在有限显存上训练大规模辐射场

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员推出了一种新颖的核外训练框架ABCD（Alpha-Composited Block Coordinate Descent），专为大规模辐射场设计，并以3D高斯溅射为例进行了演示。该方法通过将训练重构为块坐标下降，一次只激活一个参数块，从而优化内存使用。通过预渲染并将非活动区域折叠成RGBA图像，ABCD显著降低了峰值显存需求，使得在内存有限的GPU上训练大型场景成为可能。实验表明，与标准方法相比，ABCD在峰值信噪比方面仅有不到5%的下降，同时保持了高质量的重建效果。 AI

影响 降低了训练大规模辐射场的显存需求，可能促进先进3D渲染技术的更广泛应用。

排序理由 详细介绍辐射场训练新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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新的ABCD框架可在有限显存上训练大规模辐射场

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详细介绍辐射场训练新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Ka Heng Shiu, Kartic Subr ·

    ABCD：Alpha-Composited Block Coordinate Descent：大型辐射场常量显存训练

    arXiv:2608.27735v1 Announce Type: new Abstract: We present ABCD (Alpha-Composited Block Coordinate Descent), an out-of-core training framework for alpha-composited radiance fields, instantiated here for 3D Gaussian Splatting. Our method reformulates training as block coordinate d…

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