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Age Regression and Age Progressionoften shortened to AR and AP Age, are a subgenre of Transformation Fetish wherein the participant's bodily age is increased or decreased. This is often a point of plot development within many stories, with the victims usually having transformation adjusting to how self-sufficient or helpless they may be in their new state as compared to their old state. A typical Age Regression story features an adult, usually one in an esteemed position or one with many responsibilities such as a high position in a corporation or a parent of young children encountering a situation that causes him or her to become younger. Typical causes include all manner of magic and pseudo-science, though a variety of fictitious medical conditions have also been concocted by writers. In these stories the victim will gradually regress, eventually reaching the physical body of an infant or a small child, and then will "bounce," or stop regressing. In other cases, though, the virus goes beyond this, regressing the victim into a pre-natal progression or complete disappearance.


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Branches Tags. Lifespan Age Transformation Synthesis code View .

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If you spot any bias in theplease reach out to help future research! We tested our code on PyTorch 1. View code.

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Releases No releases published. Lifespan Age Transformation Synthesis is a GAN based method deed to simulate the continuous aging process from a single input image. View .

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These measures include:. This parameter controls the of interpolated frames between every 2 anchor classes. Packages 0 No packages published. This code is the official PyTorch implementation of the paper:. You can either run the demo localy or explore it in Colab.

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Git stats commits. This code requires PyTorch and torchvision to be installed, please go to PyTorch.

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Could not load tags. Failed to load latest commit information. Please refer to Using your own images for guidelines on what images are good to use.

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Increasing it will reduce the length of the output video. We have devoted considerable efforts in our algorithm de to preserve the identity of the person in the input image, and to minimize the influence of the inherent dataset biases on the .

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If any of these packages are not installed on your computer, you can install them using the supplied requirements. Reload to refresh your session. This code is inspired by pix2pix-HD and style-based-gan-pytorch. Despite these measures, the network might still introduce other biases that we did not consider when deing the algorithm.

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The task of age transformation illustrates the change of an individual's appearance over time.


Abstract We address the problem of single photo age progression and regressionthe prediction of how a person might look in the future, or how they looked in the past.


Age progression is the process of modifying a photograph of a person to represent the effect of aging on their appearance.


This paper presents a novel age transformation algorithm to handle the challenge of facial aging in face recognition.