# FSNet: An Identity-Aware Generative Model for Image-based Face Swapping

arXiv: https://arxiv.org/abs/1811.12666 · HTML: https://mlsanity.com/paper/1811.12666/

## Key facts

- Cited by 29 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Nov 2018.

## Built on by (most cited first, 29 of 29)

- [SimSwap: An Efficient Framework For High Fidelity Face Swapping](https://mlsanity.com/paper/2106.06340/) (2021)
- [One Shot Face Swapping on Megapixels](https://mlsanity.com/paper/2105.04932/) (2021)
- [HifiFace: 3D Shape and Semantic Prior Guided High Fidelity Face Swapping](https://mlsanity.com/paper/2106.09965/) (2021)
- [Deepfakes Generation and Detection: State-of-the-art, open challenges, countermeasures, and way forward](https://mlsanity.com/paper/2103.00484/) (2021)
- [High-resolution Face Swapping via Latent Semantics Disentanglement](https://mlsanity.com/paper/2203.15958/) (2022)
- [LatentAvatar: Learning Latent Expression Code for Expressive Neural Head Avatar](https://mlsanity.com/paper/2305.01190/) (2023)
- [Region-Aware Face Swapping](https://mlsanity.com/paper/2203.04564/) (2022)
- [FSGANv2: Improved Subject Agnostic Face Swapping and Reenactment](https://mlsanity.com/paper/2202.12972/) (2022)
- [Smooth-Swap: A Simple Enhancement for Face-Swapping with Smoothness](https://mlsanity.com/paper/2112.05907/) (2021)
- [Deepfake Videos in the Wild: Analysis and Detection](https://mlsanity.com/paper/2103.04263/) (2021)
- [Cross-Domain and Disentangled Face Manipulation with 3D Guidance](https://mlsanity.com/paper/2104.11228/) (2021)
- [ReSyncer: Rewiring Style-based Generator for Unified Audio-Visually Synced Facial Performer](https://mlsanity.com/paper/2408.03284/) (2024)
- [Face Transformer: Towards High Fidelity and Accurate Face Swapping](https://mlsanity.com/paper/2304.02530/) (2023)
- [Metric Learning for Anti-Compression Facial Forgery Detection](https://mlsanity.com/paper/2103.08397/) (2021)
- [ReliableSwap: Boosting General Face Swapping Via Reliable Supervision](https://mlsanity.com/paper/2306.05356/) (2023)
- [Diff-ID: An Explainable Identity Difference Quantification Framework for DeepFake Detection](https://mlsanity.com/paper/2303.18174/) (2023)
- [What makes you, you? Analyzing Recognition by Swapping Face Parts](https://mlsanity.com/paper/2206.11759/) (2022)
- [Face Swapping as A Simple Arithmetic Operation](https://mlsanity.com/paper/2211.10812/) (2022)
- [ShapeEditer: a StyleGAN Encoder for Face Swapping](https://mlsanity.com/paper/2106.13984/) (2021)
- [Robust Deepfake On Unrestricted Media: Generation And Detection](https://mlsanity.com/paper/2202.06228/) (2022)
- [Fighting Malicious Media Data: A Survey on Tampering Detection and Deepfake Detection](https://mlsanity.com/paper/2212.05667/) (2022)
- [Principles of Designing Robust Remote Face Anti-Spoofing Systems](https://mlsanity.com/paper/2406.03684/) (2024)
- [FaceTracer: Unveiling Source Identities from Swapped Face Images and Videos for Fraud Prevention](https://mlsanity.com/paper/2412.08082/) (2024)
- [BLANKET: Anonymizing Faces in Infant Video Recordings](https://mlsanity.com/paper/2512.15542/) (2025)
- [De-Fake: Style based Anomaly Deepfake Detection](https://mlsanity.com/paper/2507.03334/) (2025)
- [Dual Defense: Adversarial, Traceable, and Invisible Robust Watermarking against Face Swapping](https://mlsanity.com/paper/2310.16540/) (2023)
- [Individualized Deepfake Detection Exploiting Traces Due to Double Neural-Network Operations](https://mlsanity.com/paper/2312.08034/) (2023)
- [Deepfake for the Good: Generating Avatars through Face-Swapping with Implicit Deepfake Generation](https://mlsanity.com/paper/2402.06390/) (2024)
- [Toward Digitalization: A Secure Approach to Find a Missing Person Using Facial Recognition Technology](https://mlsanity.com/paper/2405.16683/) (2024)

## Abstract (arXiv)

This paper presents FSNet, a deep generative model for image-based face swapping. Traditionally, face-swapping methods are based on three-dimensional morphable models (3DMMs), and facial textures are replaced between the estimated three-dimensional (3D) geometries in two images of different individuals. However, the estimation of 3D geometries along with different lighting conditions using 3DMMs is still a difficult task. We herein represent the face region with a latent variable that is assigned with the proposed deep neural network (DNN) instead of facial textures. The proposed DNN synthesizes a face-swapped image using the latent variable of the face region and another image of the non-face region. The proposed method is not required to fit to the 3DMM; additionally, it performs face swapping only by feeding two face images to the proposed network. Consequently, our DNN-based face swapping performs better than previous approaches for challenging inputs with different face orientations and lighting conditions. Through several experiments, we demonstrated that the proposed method performs face swapping in a more stable manner than the state-of-the-art method, and that its results are compatible with the method thereof.