MegaPortrait: Revisiting Diffusion Control for High-fidelity Portrait Generation
Abstract
MegaPortrait, an innovative system for creating personalized portraits, utilizes Identity Net, Shading Net, and Harmonization Net modules, combined with off-the-shelf Controlnets, to achieve superior identity preservation and image fidelity compared to existing AI portrait products.
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.
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