# Lifespan Age Transformation Synthesis

arXiv: https://arxiv.org/abs/2003.09764 · HTML: https://mlsanity.com/paper/2003.09764/

## Key facts

- Cited by 60 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Mar 2020.

## Built on by (most cited first, 30 of 60)

- [Only a Matter of Style: Age Transformation Using a Style-Based Regression Model](https://mlsanity.com/paper/2102.02754/) (2021)
- [Style-Based Global Appearance Flow for Virtual Try-On](https://mlsanity.com/paper/2204.01046/) (2022)
- [BCI: Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pix](https://mlsanity.com/paper/2204.11425/) (2022)
- [Discover the Unknown Biased Attribute of an Image Classifier](https://mlsanity.com/paper/2104.14556/) (2021)
- [Generative Adversarial Registration for Improved Conditional Deformable Templates](https://mlsanity.com/paper/2105.04349/) (2021)
- [Rewriting Geometric Rules of a GAN](https://mlsanity.com/paper/2207.14288/) (2022)
- [MOST-GAN: 3D Morphable StyleGAN for Disentangled Face Image Manipulation](https://mlsanity.com/paper/2111.01048/) (2021)
- [Face Aging via Diffusion-based Editing](https://mlsanity.com/paper/2309.11321/) (2023)
- [Revisiting the Importance of Amplifying Bias for Debiasing](https://mlsanity.com/paper/2205.14594/) (2022)
- [Custom Structure Preservation in Face Aging](https://mlsanity.com/paper/2207.11025/) (2022)
- [Ethical Considerations for Responsible Data Curation](https://mlsanity.com/paper/2302.03629/) (2023)
- [Pluralistic Aging Diffusion Autoencoder](https://mlsanity.com/paper/2303.11086/) (2023)
- [Beyond Skin Tone: A Multidimensional Measure of Apparent Skin Color](https://mlsanity.com/paper/2309.05148/) (2023)
- [Scaling-up Disentanglement for Image Translation](https://mlsanity.com/paper/2103.14017/) (2021)
- [Disentangled Lifespan Face Synthesis](https://mlsanity.com/paper/2108.02874/) (2021)
- [What's in a Decade? Transforming Faces Through Time](https://mlsanity.com/paper/2210.06642/) (2022)
- [Adaptive Nonlinear Latent Transformation for Conditional Face Editing](https://mlsanity.com/paper/2307.07790/) (2023)
- [Continuous Face Aging via Self-estimated Residual Age Embedding](https://mlsanity.com/paper/2105.00020/) (2021)
- [When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework and A New Benchmark](https://mlsanity.com/paper/2210.09835/) (2022)
- [Projected Coupled Diffusion for Test-Time Constrained Joint Generation](https://mlsanity.com/paper/2508.10531/) (2025)
- [Delving into the Continuous Domain Adaptation](https://mlsanity.com/paper/2208.13121/) (2022)
- [A View From Somewhere: Human-Centric Face Representations](https://mlsanity.com/paper/2303.17176/) (2023)
- [Child Face Recognition at Scale: Synthetic Data Generation and Performance Benchmark](https://mlsanity.com/paper/2304.11685/) (2023)
- [DiffAge3D: Diffusion-based 3D-aware Face Aging](https://mlsanity.com/paper/2408.15922/) (2024)
- [DAA: A Delta Age AdaIN operation for age estimation via binary code transformer](https://mlsanity.com/paper/2303.07929/) (2023)
- [MyTimeMachine: Personalized Facial Age Transformation](https://mlsanity.com/paper/2411.14521/) (2024)
- [Bias Amplification in Stable Diffusion's Representation of Stigma Through Skin Tones and Their Homogeneity](https://mlsanity.com/paper/2508.17465/) (2025)
- [K-FACE: A Large-Scale KIST Face Database in Consideration with Unconstrained Environments](https://mlsanity.com/paper/2103.02211/) (2021)
- [Harnessing the Conditioning Sensorium for Improved Image Translation](https://mlsanity.com/paper/2110.06443/) (2021)
- [A comprehensive survey on semantic facial attribute editing using generative adversarial networks](https://mlsanity.com/paper/2205.10587/) (2022)

## Abstract (arXiv)

We address the problem of single photo age progression and regression-the prediction of how a person might look in the future, or how they looked in the past. Most existing aging methods are limited to changing the texture, overlooking transformations in head shape that occur during the human aging and growth process. This limits the applicability of previous methods to aging of adults to slightly older adults, and application of those methods to photos of children does not produce quality results. We propose a novel multi-domain image-to-image generative adversarial network architecture, whose learned latent space models a continuous bi-directional aging process. The network is trained on the FFHQ dataset, which we labeled for ages, gender, and semantic segmentation. Fixed age classes are used as anchors to approximate continuous age transformation. Our framework can predict a full head portrait for ages 0-70 from a single photo, modifying both texture and shape of the head. We demonstrate results on a wide variety of photos and datasets, and show significant improvement over the state of the art.