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English(EN) Gate3DGen: A Pre-processing Model that Selectively Purifies Real-World Images for 3D Generation

Gate3DGen模型净化真实世界图像以改进3D生成

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了Gate3DGen，这是一种新颖的预处理模型，旨在提高从真实世界图像生成3D的准确性。该模型选择性地识别和净化降质图像（例如光照不良或有遮挡的图像），而无需重新训练现有的3D生成器。Gate3DGen利用一个感知降质的路由器来区分干净和损坏的输入，并对后者应用专门的净化器。此过程旨在保留物体身份和轮廓等关键视觉线索，从而提高3D几何形状和保真度。 AI

影响 该模型可以显著提高从各种真实世界图像数据集中生成的3D内容的质量和可靠性。

排序理由 该集群描述了一篇关于用于3D生成中图像处理的新颖模型的新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

Gate3DGen模型净化真实世界图像以改进3D生成

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该集群描述了一篇关于用于3D生成中图像处理的新颖模型的新研究论文。[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) · Xiaolin Li, Zihao Huang, Fanpeng Meng, Chen Yang, Guanjun Wu, Kai Zhang, Jiemin Fang, Qi Tian ·

    Gate3DGen: A Pre-processing Model that Selectively Purifies Real-World Images for 3D Generation

    arXiv:2610.31649v1 Announce Type: new Abstract: Single-image 3D generation has achieved high fidelity on curated benchmarks, yet degrades sharply on real-world images with uneven illumination, blur, and occlusions. Purifying such inputs requires deciding when to intervene and pre…

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