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Max Bluvstein

1 accepted papers

2026

Realiz3D: 3D Generation Made Photorealistic via Domain-Aware Learning

CVPR 2026

We often aim to generate images that are both photorealistic and 3D-consistent, adhering to precise geometry, material, and viewpoint controls. Typically, this is achieved by fine-tuning an image generator, pre-trained on billions of real images, using renders of synthetic 3D assets, where annotatio

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