DeepAI AI Chat
Log In Sign Up

Recursive Chaining of Reversible Image-to-image Translators For Face Aging

by   Ari Heljakka, et al.

This paper addresses the modeling and simulation of progressive changes over time, such as human face aging. By treating the age phases as a sequence of image domains, we construct a chain of transformers that map images from one age domain to the next. Leveraging recent adversarial image translation methods, our approach requires no training samples of the same individual at different ages. Here, the model must be flexible enough to translate a child face to a young adult, and all the way through the adulthood to old age. We find that some transformers in the chain can be recursively applied on their own output to cover multiple phases, compressing the chain. The structure of the chain also unearths information about the underlying physical process. We demonstrate the performance of our method with precise and intuitive metrics, and visually match with the face aging state-of-the-art.


page 1

page 6


How Old Are You? Face Age Translation with Identity Preservation Using GANs

We present a novel framework to generate images of different age while p...

ITTR: Unpaired Image-to-Image Translation with Transformers

Unpaired image-to-image translation is to translate an image from a sour...

Generative Reversible Data Hiding by Image to Image Translation via GANs

The traditional reversible data hiding technique is based on cover image...

Facial age estimation using BSIF and LBP

Human face aging is irreversible process causing changes in human face c...

Age Progression and Regression with Spatial Attention Modules

Age progression and regression refers to aesthetically rendering a given...

Somewhat Reversible Data Hiding by Image to Image Translation

The traditional reversible data hiding technique is based on image modif...

Analysis of the Human-Computer Interaction on the Example of Image-based CAPTCHA by Association Rule Mining

The paper analyzes the interaction between humans and computers in terms...