Abstract
We propose MegaPortrait. It's an innovative system for creating personalized portrait images in computer vision. It has three modules: Identity Net, Shading Net, and Harmonization Net. Identity Net generates learned identity using a customized model fine-tuned with source images. Shading Net re-renders portraits using extracted representations. Harmonization Net fuses pasted faces and the reference image's body for coherent results. Our approach with off-the-shelf Controlnets is better than state-of-the-art AI portrait products in identity preservation and image fidelity. MegaPortrait has a simple but effective design and we compare it with other methods and products to show its superiority.
Abstract (translated)
我们提出了一种名为MegaPortrait的系统，这是一种用于计算机视觉中创建个性化肖像图像的创新性系统。该系统包括三个模块：Identity Net（身份网络）、Shading Net（阴影网络）和Harmonization Net（和谐网络）。Identity Net利用经过源图像微调的定制模型生成学习到的身份特征。Shading Net使用提取的表示重新渲染肖像。Harmonization Net融合粘贴的脸部与参考图像的身体部分，以获得一致的结果。我们的方法结合现成的Controlnets，在身份保持和图像保真度方面优于现有的AI肖像产品。MegaPortrait的设计简单而有效，并且我们将其与其他方法和产品进行了比较，证明了其优越性。
URL
https://arxiv.org/abs/2411.04357
