Morphable Diffusion: 3D-Consistent Diffusion for Single-image Avatar Creation

التفاصيل البيبلوغرافية
العنوان: Morphable Diffusion: 3D-Consistent Diffusion for Single-image Avatar Creation
المؤلفون: Chen, Xiyi, Mihajlovic, Marko, Wang, Shaofei, Prokudin, Sergey, Tang, Siyu
سنة النشر: 2024
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
الوصف: Recent advances in generative diffusion models have enabled the previously unfeasible capability of generating 3D assets from a single input image or a text prompt. In this work, we aim to enhance the quality and functionality of these models for the task of creating controllable, photorealistic human avatars. We achieve this by integrating a 3D morphable model into the state-of-the-art multi-view-consistent diffusion approach. We demonstrate that accurate conditioning of a generative pipeline on the articulated 3D model enhances the baseline model performance on the task of novel view synthesis from a single image. More importantly, this integration facilitates a seamless and accurate incorporation of facial expression and body pose control into the generation process. To the best of our knowledge, our proposed framework is the first diffusion model to enable the creation of fully 3D-consistent, animatable, and photorealistic human avatars from a single image of an unseen subject; extensive quantitative and qualitative evaluations demonstrate the advantages of our approach over existing state-of-the-art avatar creation models on both novel view and novel expression synthesis tasks. The code for our project is publicly available.
Comment: [CVPR 2024] Project page: https://xiyichen.github.io/morphablediffusionTest/
نوع الوثيقة: Working Paper
الوصول الحر: http://arxiv.org/abs/2401.04728Test
رقم الانضمام: edsarx.2401.04728
قاعدة البيانات: arXiv