Feb. 6, 2024, 5:46 a.m. | Bernard Spiegl Andrea Perin St\'ephane Deny Alexander Ilin

cs.LG updates on arXiv.org arxiv.org

Deep learning is providing a wealth of new approaches to the old problem of novel view synthesis, from Neural Radiance Field (NeRF) based approaches to end-to-end style architectures. Each approach offers specific strengths but also comes with specific limitations in their applicability. This work introduces ViewFusion, a state-of-the-art end-to-end generative approach to novel view synthesis with unparalleled flexibility. ViewFusion consists in simultaneously applying a diffusion denoising step to any number of input views of a scene, then combining the noise …

architectures art cs.cv cs.lg deep learning diffusion diffusion models generative limitations nerf neural radiance field novel state style synthesis view wealth work

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