Morphable Diffusion: 3D-Consistent Diffusion for Single-image Avatar Creation
Xiyi Chen, Marko Mihajlovic, Shaofei Wang, Sergey Prokudin, Siyu Tang
2024年份
9顶会引用
摘要
4 https://xiyichen.github.io/morphablediffusion/ Figure 1. Morphable diffusion. We introduce a morphable diffusion model to enable consistent controllable novel view synthesis of humans from a single image. Given a single input image (a) and a morphable mesh model with a target facial expression (b) our method directly generates 3D consistent and photo-realistic images from novel viewpoints (c). Using the generated multi-view consistent images, we can reconstruct a coarse 3D model (d) using off-the-shelf neural surface reconstruction methods such as [80].
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引用它的顶会 Paper9
- CGS-GAN: 3D Consistent Gaussian Splatting GANs for High Resolution Human Head SynthesisFlorian Barthel, Wieland Morgenstern, Paul Hinzer, Anna Hilsmann 等NeurIPS 2025 · 被引用 8 次
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- SpinMeRound: Consistent Multi-View Identity Generation Using Diffusion ModelsStathis Galanakis, Alexandros Lattas, Stylianos Moschoglou, Bernhard Kainz 等ICCV 2025 · 被引用 3 次
- Fine-Grained 3D Gaussian Head Avatars Modeling from Static Captures Via Joint Reconstruction and RegistrationYuan Sun, Xuan Wang, Cong Wang, Weili Zhang 等ICCV 2025 · 被引用 1 次
- Anti-Avatar: Protect Against Unauthorized 3D Head Avatar Generation via Dual-Space DivergenceLingzhuang Meng, Mingwen Shao, Xiang Lv, Mengyao Wu 等AAAI 2026 · 被引用 1 次
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