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MVDiff: Scalable and Flexible Multi-View Diffusion for 3D Object Reconstruction from Single-View

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arxiv 2405.03894 v2 pith:EZ73VFLN submitted 2024-05-06 cs.CV cs.LG

classification cs.CVcs.LG
keywords modeldiffusionmulti-viewconsistentgenerateimagereconstructionable
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Generating consistent multiple views for 3D reconstruction tasks is still a challenge to existing image-to-3D diffusion models. Generally, incorporating 3D representations into diffusion model decrease the model's speed as well as generalizability and quality. This paper proposes a general framework to generate consistent multi-view images from single image or leveraging scene representation transformer and view-conditioned diffusion model. In the model, we introduce epipolar geometry constraints and multi-view attention to enforce 3D consistency. From as few as one image input, our model is able to generate 3D meshes surpassing baselines methods in evaluation metrics, including PSNR, SSIM and LPIPS.

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Cited by 1 Pith paper

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  1. Eval3D: Interpretable and Fine-grained Evaluation for 3D Generation

    cs.CV 2025-04 conditional novelty 6.0 of 10

    Eval3D measures 3D generation quality through consistency among foundation models, delivering fine-grained scores and 3D artifact localization that align with human judgments.

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