RealFusion 360° Reconstruction of Any Object from a Single Image
Luke Melas-Kyriazi, Iro Laina, Christian Rupprecht, Andrea Vedaldi
2023年份
59顶会引用
摘要
https://lukemelas.github.io/realfusion Figure 1. RealFusion generates a full 360 • reconstruction of any object given a single image of it (left column). It does so by leveraging an existing diffusion-based 2D image generator. From the given image, it synthesizes a prompt that causes the diffusion model to "dream up" other views of the object. It then extracts a neural radiance field from the original image and the diffusion model-based prior, thereby reconstructing the object in full. Both appearance and geometry are reconstructed faithfully and extrapolated in a plausible manner.
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引用它的顶会 Paper59
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它引用的顶会 Paper30
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- Photorealistic Text-to-Image Diffusion Models with Deep Language UnderstandingChitwan Saharia, William Chan, Saurabh Saxena, Lala Li 等NeurIPS 2022 · 被引用 8,965 次
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