hfgi

Maintainer: tengfei-wang

Total Score

22

Last updated 5/17/2024
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Paper LinkView on Arxiv

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Model overview

HFGI is a novel high-fidelity GAN inversion framework that enables attribute editing with image-specific details well-preserved, such as background, appearance, and illumination. It was developed by Tengfei Wang and colleagues, and published at CVPR 2022. The model is similar to other face restoration and editing models like GFPGAN and GFPGAN, as well as general image synthesis models like Stable Diffusion and SwinIR, in that they all aim to generate high-quality images. However, HFGI is specifically focused on preserving fine details during attribute editing.

Model inputs and outputs

HFGI takes an input image and allows the user to edit various attributes like age, smile, eyes, lips, and beard. The degree of editing can also be controlled. The output is the edited image with the specified attributes changed while maintaining the original details.

Inputs

  • Image: The input image to be edited
  • Edit Degree: A value between -5 and 5 that controls the degree of editing for attributes like age and smile

Outputs

  • Edited Image: The output image with the specified attributes edited

Capabilities

HFGI can perform high-fidelity GAN inversion, which means it can accurately reconstruct the latent representation of an input image in the GAN's latent space. This allows it to edit specific attributes of the image, such as age, smile, eyes, lips, and beard, while preserving the original details like background, appearance, and illumination.

What can I use it for?

You can use HFGI for a variety of image editing tasks, such as touch-ups, retouching, and digital makeovers. For example, you could use it to make minor adjustments to a portrait photo, such as changing the subject's expression or age, without losing the realistic details of the original image. This could be useful for personal photo editing, as well as commercial applications like fashion and advertising.

Things to try

One interesting thing to try with HFGI is exploring the limits of its attribute editing capabilities. You could experiment with pushing the "Edit Degree" parameter to the extremes, or trying to edit multiple attributes simultaneously, to see how the model handles more complex edits while maintaining high fidelity. Additionally, you could try using HFGI in combination with other image processing tools, such as super-resolution or style transfer, to further enhance the edited results.



This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!

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