Yuval-alaluf
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Number of Runs: 625,777
Models by this creator
sam
The model presented in this research paper is a style-based regression model for age transformation in images. It takes an input image of a person and predicts the age appearance of that person in the image using a novel style-based regression approach. This approach considers the style of an input image, such as the facial appearance, and uses it to predict the age appearance of the person in the image. The model is trained on a large dataset of labeled age images, and it achieves state-of-the-art performance on various evaluation metrics.
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restyle_encoder
restyle_encoder
The restyle_encoder is an image-to-image model that uses a residual-based StyleGAN encoder through a process of iterative refinement. By feeding the model a specific image URL, specifying an encoding type, choosing the number of iterations, and deciding whether to display intermediate results, it produces a transformed version of the original image. The outcome of this processing is another URL hosting the output image. This model can be used for a variety of image transformation purposes, including toonification.
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restyle_encoder
restyle_encoder
The restyle_encoder is an image-to-image model that works based on the ReStyle concept, a residual-based StyleGAN encoder that iteratively refines the output. It's used to process an image and transform it according to a chosen encoding type, for example, 'toonify'. The number of iterations and whether to display intermediate results are customizable inputs. Inputs to the model are URL images and the model outputs the URL of the transformed image.
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restyle_​encoder
The restyle_encoder model is an image-to-image model that aims to encode the style of an input image and transfer it to a different target image. It uses a residual-based approach and iterative refinement to achieve this. The model takes an input image and a target image as input and outputs an encoded image that has the same style as the input image and the same content as the target image. This model is useful for style transfer tasks where the style of one image is desired on the content of another image.
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