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GAE: Learning a Geometry-Native Latent Space for 3D-Consistent World Generation

The paper introduces GAE, a geometry-native latent space for 3D-consistent world generation. It proposes reparameterizing a geometry foundation model's features into a compact latent space that enables joint decoding of appearance, depth, cameras, and point maps, improving visual quality and 3D coherence compared to traditional methods.

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PublishedSeptember 21, 2026Jiahao Lu, Minghao Yin, Wenbo Hu
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WHY IT MAY MATTER

This approach could improve 3D generation tasks by providing a shared latent space that better captures geometric consistency, potentially leading to more realistic and coherent 3D environments.

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