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CVPR2025Top-tier venue

Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion

Vitor Guizilini, Muhammad Zubair Irshad, Dian Chen, Greg Shakhnarovich, Rares Ambrus

2025Year
4Top-tier citations

Abstract

Figure 1 . MVGD is a state-of-the-art method that generates images and scale-consistent depth maps from novel viewpoints given an arbitrary number of posed input views. In the above, red cameras are used as conditioning to directly generate RGB-D predictions from green cameras. To highlight the multi-view consistency of our method, predicted colored pointclouds from all novel viewpoints are stacked together for visualization without any post-processing. More examples and videos can be found in https://mvgd.github.io/

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