English(EN) Latent Bridge: From Video Latents to 3D Geometry via Feature Alignment

新方法直接从视频潜在表示预测3D几何

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-21 04:00

研究人员推出了Latent Bridge，一种直接从视频生成潜在空间预测3D几何的新颖方法。该方法绕过了中间RGB解码和重新编码的需要，实现了更高效的端到端生成和重建。Latent Bridge利用特定于表示的桥接器，适用于Wan2.1和V-RAE等模型，能够前馈预测相机、深度和3D点云。该方法在Co3Dv2和WildRGB-D等数据集上展示了具有竞争力的几何重建质量，并且训练好的桥接器可重用于不同的视频生成任务，无需重新训练。 AI

影响能够从生成的视频中更有效地进行3D重建，可能加速计算机图形学和虚拟现实领域的流程。

排序理由该集群包含一篇研究论文，详细介绍了一种从视频潜在表示预测3D几何的新方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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报道来源 [1]

arXiv cs.CV TIER_1 English(EN) · Shuai Zhang, Zhanpeng Ouyang, Zhengqing Chen, Ruohong Mei, Shaoyu Chen, Weiqiang Ren, Hui Sun, Qian Zhang, Wenyu Liu, Xinggang Wang · 2026-10-21 04:00

Latent Bridge：从视频隐变量到三维几何的特征对齐

arXiv:2610.28521v1 Announce Type: new Abstract: Video generation and feed-forward 3D reconstruction typically use separate representations, requiring RGB decoding and visual re-encoding to recover geometry from generated latents. We propose Latent Bridge, which connects video gen…

本文如何被排名

报道来源 [1]

Latent Bridge：从视频隐变量到三维几何的特征对齐

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