# Time-Travel Rephotography

arXiv: https://arxiv.org/abs/2012.12261 · HTML: https://mlsanity.com/paper/2012.12261/

## Key facts

- Cited by 26 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Dec 2020.

## Built on by (most cited first, 26 of 26)

- [Labels4Free: Unsupervised Segmentation using StyleGAN](https://mlsanity.com/paper/2103.14968/) (2021)
- [StyleAlign: Analysis and Applications of Aligned StyleGAN Models](https://mlsanity.com/paper/2110.11323/) (2021)
- [Spatially-Adaptive Multilayer Selection for GAN Inversion and Editing](https://mlsanity.com/paper/2206.08357/) (2022)
- [State-of-the-Art in the Architecture, Methods and Applications of StyleGAN](https://mlsanity.com/paper/2202.14020/) (2022)
- [BigColor: Colorization using a Generative Color Prior for Natural Images](https://mlsanity.com/paper/2207.09685/) (2022)
- [MyStyle: A Personalized Generative Prior](https://mlsanity.com/paper/2203.17272/) (2022)
- [Robust Unsupervised StyleGAN Image Restoration](https://mlsanity.com/paper/2302.06733/) (2023)
- [InstantRestore: Single-Step Personalized Face Restoration with Shared-Image Attention](https://mlsanity.com/paper/2412.06753/) (2024)
- [Panini-Net: GAN Prior Based Degradation-Aware Feature Interpolation for Face Restoration](https://mlsanity.com/paper/2203.08444/) (2022)
- [StyleDomain: Efficient and Lightweight Parameterizations of StyleGAN for One-shot and Few-shot Domain Adaptation](https://mlsanity.com/paper/2212.10229/) (2022)
- [What's in a Decade? Transforming Faces Through Time](https://mlsanity.com/paper/2210.06642/) (2022)
- [Synthesis and Reconstruction of Fingerprints using Generative Adversarial Networks](https://mlsanity.com/paper/2201.06164/) (2022)
- [Modernizing Old Photos Using Multiple References via Photorealistic Style Transfer](https://mlsanity.com/paper/2304.04461/) (2023)
- [Spectral Sensitivity Estimation Without a Camera](https://mlsanity.com/paper/2304.11549/) (2023)
- [Personalized Restoration via Dual-Pivot Tuning](https://mlsanity.com/paper/2312.17234/) (2023)
- [How to Guide Adaptive Depth Sampling?](https://mlsanity.com/paper/2205.10202/) (2022)
- [Descanning: From Scanned to the Original Images with a Color Correction Diffusion Model](https://mlsanity.com/paper/2402.05350/) (2024)
- [Snapmoji: Instant Generation of Animatable Dual-Stylized Avatars](https://mlsanity.com/paper/2503.11978/) (2025)
- [Linearly Constrained Diffusion Implicit Models](https://mlsanity.com/paper/2411.00359/) (2024)
- [Towards a Universal Image Degradation Model via Content-Degradation Disentanglement](https://mlsanity.com/paper/2505.12860/) (2025)
- [Influence of Color Spaces for Deep Learning Image Colorization](https://mlsanity.com/paper/2204.02850/) (2022)
- [Facial Reenactment Through a Personalized Generator](https://mlsanity.com/paper/2307.06307/) (2023)
- [Continual Learning of Personalized Generative Face Models with Experience Replay](https://mlsanity.com/paper/2412.02627/) (2024)
- [CaMiT: A Time-Aware Car Model Dataset for Classification and Generation](https://mlsanity.com/paper/2510.17626/) (2025)
- [MDTD-ArtIR: Benchmarking Image Editing and Restoration Models for Art Image Restoration under Texture-Overlay Degradations](https://mlsanity.com/paper/2608.00736/) (2026)
- [Beyond Fixed Luminance: Towards Panchromatic and Orthochromatic Image Colorization](https://mlsanity.com/paper/2608.10798/) (2026)

## Abstract (arXiv)

Many historical people were only ever captured by old, faded, black and white photos, that are distorted due to the limitations of early cameras and the passage of time. This paper simulates traveling back in time with a modern camera to rephotograph famous subjects. Unlike conventional image restoration filters which apply independent operations like denoising, colorization, and superresolution, we leverage the StyleGAN2 framework to project old photos into the space of modern high-resolution photos, achieving all of these effects in a unified framework. A unique challenge with this approach is retaining the identity and pose of the subject in the original photo, while discarding the many artifacts frequently seen in low-quality antique photos. Our comparisons to current state-of-the-art restoration filters show significant improvements and compelling results for a variety of important historical people.