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English(EN) PixSDS: Why Latent SDS Makes Noisy Pixels

PixSDS方法减少文本到3D生成中的伪影

研究人员开发了PixSDS,这是一种解决文本到3D生成中由潜在得分蒸馏采样(SDS)引起的伪影的新方法。该技术通过使用解码图像方向来指导优化,从而减少噪声并保留语义内容,从而解决VAE引起的像素漂移。PixSDS无需重新训练扩散模型或更改渲染器即可运行,为提高生成3D资产的质量提供了一种轻量级解决方案。 AI

影响 该方法可能导致从文本提示生成的3D模型质量更高且伪影更少。

排序理由 该集群描述了一篇详细介绍改进3D生成新方法的最新研究论文。

在 Hugging Face Daily Papers 阅读 →

AI 生成摘要 · Google Gemini · 来自 3 个来源。 我们如何撰写摘要 →

PixSDS方法减少文本到3D生成中的伪影

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报道来源 [3]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    PixSDS:为什么潜在的SDS会产生噪点像素

    Score Distillation Sampling (SDS) enables text-to-3D generation by optimizing rendered images with a pretrained diffusion prior, but latent SDS often produces structured color artifacts and high-frequency texture noise. We identify a failure mode of latent SDS caused by VAE-induc…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    PixSDS:为什么潜在的SDS会产生噪声像素

    PixSDS fixes VAE-induced pixel drift in latent score distillation sampling by guiding optimization with decoded image directions, reducing artifacts in text-to-3D generation.

  3. arXiv cs.CV TIER_1 English(EN) · Vsevolod Skorokhodov ·

    PixSDS:为什么潜在的SDS会产生噪声像素

    arXiv:2608.12997v1 Announce Type: new Abstract: Score Distillation Sampling (SDS) enables text-to-3D generation by optimizing rendered images with a pretrained diffusion prior, but latent SDS often produces structured color artifacts and high-frequency texture noise. We identify …