# Face Aging via Diffusion-based Editing arXiv: https://arxiv.org/abs/2309.11321 ยท HTML: https://mlsanity.com/paper/2309.11321/ ## Key facts - Cited by 24 papers in the map (data through 14 Oct 2026). - Placed in Image generation, text-to-image and editing, one of 14 directions in Diffusion models. - Builds on 36 of its 43 references that are in the map. - First posted on arXiv 20 Sep 2023. ## Placed in - Diffusion models / [Image generation, text-to-image and editing](https://mlsanity.com/diffusion/image-generation-text-to-image-and-editing/) ## Builds on (most cited first, 30 of 36) - [Denoising Diffusion Probabilistic Models](https://mlsanity.com/paper/2006.11239/) (2020) - [High-Resolution Image Synthesis with Latent Diffusion Models](https://mlsanity.com/paper/2112.10752/) (2021) - [Denoising Diffusion Implicit Models](https://mlsanity.com/paper/2010.02502/) (2020) - [Hierarchical Text-Conditional Image Generation with CLIP Latents](https://mlsanity.com/paper/2204.06125/) (2022) - [Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding](https://mlsanity.com/paper/2205.11487/) (2022) - [A Style-Based Generator Architecture for Generative Adversarial Networks](https://mlsanity.com/paper/1812.04948/) (2018) - [Generative Adversarial Networks](https://mlsanity.com/paper/2203.00667/) (2022) - [Deep Learning Face Attributes in the Wild](https://mlsanity.com/paper/1411.7766/) (2014) - [GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models](https://mlsanity.com/paper/2112.10741/) (2021) - [Analyzing and Improving the Image Quality of StyleGAN](https://mlsanity.com/paper/1912.04958/) (2019) - [Progressive Growing of GANs for Improved Quality, Stability, and Variation](https://mlsanity.com/paper/1710.10196/) (2017) - [Prompt-to-Prompt Image Editing with Cross Attention Control](https://mlsanity.com/paper/2208.01626/) (2022) - [Conditional Generative Adversarial Nets](https://mlsanity.com/paper/1411.1784/) (2014) - [SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations](https://mlsanity.com/paper/2108.01073/) (2021) - [LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs](https://mlsanity.com/paper/2111.02114/) (2021) - [Demystifying MMD GANs](https://mlsanity.com/paper/1801.01401/) (2018) - [Null-text Inversion for Editing Real Images using Guided Diffusion Models](https://mlsanity.com/paper/2211.09794/) (2022) - [Imagic: Text-Based Real Image Editing with Diffusion Models](https://mlsanity.com/paper/2210.09276/) (2022) - [Blended Diffusion for Text-driven Editing of Natural Images](https://mlsanity.com/paper/2111.14818/) (2021) - [Interpreting the Latent Space of GANs for Semantic Face Editing](https://mlsanity.com/paper/1907.10786/) (2019) - [DiffEdit: Diffusion-based semantic image editing with mask guidance](https://mlsanity.com/paper/2210.11427/) (2022) - [GANSpace: Discovering Interpretable GAN Controls](https://mlsanity.com/paper/2004.02546/) (2020) - [Designing an Encoder for StyleGAN Image Manipulation](https://mlsanity.com/paper/2102.02766/) (2021) - [Blended Latent Diffusion](https://mlsanity.com/paper/2206.02779/) (2022) - [Age Progression/Regression by Conditional Adversarial Autoencoder](https://mlsanity.com/paper/1702.08423/) (2017) - [What the DAAM: Interpreting Stable Diffusion Using Cross Attention](https://mlsanity.com/paper/2210.04885/) (2022) - [Fader Networks: Manipulating Images by Sliding Attributes](https://mlsanity.com/paper/1706.00409/) (2017) - [Only a Matter of Style: Age Transformation Using a Style-Based Regression Model](https://mlsanity.com/paper/2102.02754/) (2021) - [Lifespan Age Transformation Synthesis](https://mlsanity.com/paper/2003.09764/) (2020) - [Face Aging With Conditional Generative Adversarial Networks](https://mlsanity.com/paper/1702.01983/) (2017) ## Built on by (most cited first, 24 of 24) - [Diffusion Model-Based Image Editing: A Survey](https://mlsanity.com/paper/2402.17525/) (2024) - [Conditional Image Synthesis with Diffusion Models: A Survey](https://mlsanity.com/paper/2409.19365/) (2024) - [DiffusionAct: Controllable Diffusion Autoencoder for One-shot Face Reenactment](https://mlsanity.com/paper/2403.17217/) (2024) - [SDFD: Building a Versatile Synthetic Face Image Dataset with Diverse Attributes](https://mlsanity.com/paper/2404.17255/) (2024) - [DiffAge3D: Diffusion-based 3D-aware Face Aging](https://mlsanity.com/paper/2408.15922/) (2024) - [MyTimeMachine: Personalized Facial Age Transformation](https://mlsanity.com/paper/2411.14521/) (2024) - [Video Face Re-Aging: Toward Temporally Consistent Face Re-Aging](https://mlsanity.com/paper/2311.11642/) (2023) - [Diverse and Lifespan Facial Age Transformation Synthesis with Identity Variation Rationality Metric](https://mlsanity.com/paper/2401.14036/) (2024) - [Synthetic Face Ageing: Evaluation, Analysis and Facilitation of Age-Robust Facial Recognition Algorithms](https://mlsanity.com/paper/2406.06932/) (2024) - [From Cradle to Cane: A Two-Pass Framework for High-Fidelity Lifespan Face Aging](https://mlsanity.com/paper/2506.20977/) (2025) - [AgeBooth: Controllable Facial Aging and Rejuvenation via Diffusion Models](https://mlsanity.com/paper/2510.05715/) (2025) - [ToonAging: Face Re-Aging upon Artistic Portrait Style Transfer](https://mlsanity.com/paper/2402.02733/) (2024) - [SelfAge: Personalized Facial Age Transformation Using Self-reference Images](https://mlsanity.com/paper/2502.13987/) (2025) - [The Aging Multiverse: Generating Condition-Aware Facial Aging Tree via Training-Free Diffusion](https://mlsanity.com/paper/2506.21008/) (2025) - [Mitigating the Impact of Attribute Editing on Face Recognition](https://mlsanity.com/paper/2403.08092/) (2024) - [TimeMachine: Fine-Grained Facial Age Editing with Identity Preservation](https://mlsanity.com/paper/2508.11284/) (2025) - [Face Time Traveller : Travel Through Ages Without Losing Identity](https://mlsanity.com/paper/2602.22819/) (2026) - [Locally Controlled Face Aging with Latent Diffusion Models](https://mlsanity.com/paper/2507.21600/) (2025) - [A Race Bias Free Face Aging Model for Reliable Kinship Verification](https://mlsanity.com/paper/2509.15177/) (2025) - [U-Face: An Efficient and Generalizable Framework for Unsupervised Facial Attribute Editing via Subspace Learning](https://mlsanity.com/paper/2603.14004/) (2026) - [MeInTime: Bridging Age Gap in Identity-Preserving Face Restoration](https://mlsanity.com/paper/2603.18645/) (2026) - [TimeWeaver: Age-Consistent Reference-Based Face Restoration with Identity Preservation](https://mlsanity.com/paper/2603.22701/) (2026) - [DiverAge: Reliable Pluralistic Face Aging with Cross-Age Identity Relation Guidance](https://mlsanity.com/paper/2606.04881/) (2026) - [ReAge3D: Re-Aging 3D Faces with View Consistency](https://mlsanity.com/paper/2606.18156/) (2026) ## Abstract (arXiv) In this paper, we address the problem of face aging: generating past or future facial images by incorporating age-related changes to the given face. Previous aging methods rely solely on human facial image datasets and are thus constrained by their inherent scale and bias. This restricts their application to a limited generatable age range and the inability to handle large age gaps. We propose FADING, a novel approach to address Face Aging via DIffusion-based editiNG. We go beyond existing methods by leveraging the rich prior of large-scale language-image diffusion models. First, we specialize a pre-trained diffusion model for the task of face age editing by using an age-aware fine-tuning scheme. Next, we invert the input image to latent noise and obtain optimized null text embeddings. Finally, we perform text-guided local age editing via attention control. The quantitative and qualitative analyses demonstrate that our method outperforms existing approaches with respect to aging accuracy, attribute preservation, and aging quality.