# StableIdentity: Inserting Anybody into Anywhere at First Sight

arXiv: https://arxiv.org/abs/2401.15975 · HTML: https://mlsanity.com/paper/2401.15975/

## Key facts

- Cited by 35 papers in the map (data through 14 Oct 2026).
- Builds on 58 of its 75 references that are in the map.
- First posted on arXiv 29 Jan 2024.

## Builds on (most cited first, 30 of 58)

- [Learning Transferable Visual Models From Natural Language Supervision](https://mlsanity.com/paper/2103.00020/) (2021)
- [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://mlsanity.com/paper/2010.11929/) (2020)
- [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)
- [The Unreasonable Effectiveness of Deep Features as a Perceptual Metric](https://mlsanity.com/paper/1801.03924/) (2018)
- [Denoising Diffusion Implicit Models](https://mlsanity.com/paper/2010.02502/) (2020)
- [Score-Based Generative Modeling through Stochastic Differential Equations](https://mlsanity.com/paper/2011.13456/) (2020)
- [Diffusion Models Beat GANs on Image Synthesis](https://mlsanity.com/paper/2105.05233/) (2021)
- [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)
- [3D Gaussian Splatting for Real-Time Radiance Field Rendering](https://mlsanity.com/paper/2308.04079/) (2023)
- [Scalable Diffusion Models with Transformers](https://mlsanity.com/paper/2212.09748/) (2022)
- [A Style-Based Generator Architecture for Generative Adversarial Networks](https://mlsanity.com/paper/1812.04948/) (2018)
- [Classifier-Free Diffusion Guidance](https://mlsanity.com/paper/2207.12598/) (2022)
- [Adding Conditional Control to Text-to-Image Diffusion Models](https://mlsanity.com/paper/2302.05543/) (2023)
- [SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis](https://mlsanity.com/paper/2307.01952/) (2023)
- [GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models](https://mlsanity.com/paper/2112.10741/) (2021)
- [DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation](https://mlsanity.com/paper/2208.12242/) (2022)
- [Taming Transformers for High-Resolution Image Synthesis](https://mlsanity.com/paper/2012.09841/) (2020)
- [Large Scale GAN Training for High Fidelity Natural Image Synthesis](https://mlsanity.com/paper/1809.11096/) (2018)
- [Prompt-to-Prompt Image Editing with Cross Attention Control](https://mlsanity.com/paper/2208.01626/) (2022)
- [An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion](https://mlsanity.com/paper/2208.01618/) (2022)
- [LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs](https://mlsanity.com/paper/2111.02114/) (2021)
- [IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models](https://mlsanity.com/paper/2308.06721/) (2023)
- [T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models](https://mlsanity.com/paper/2302.08453/) (2023)
- [Frozen in Time: A Joint Video and Image Encoder for End-to-End Retrieval](https://mlsanity.com/paper/2104.00650/) (2021)
- [Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields](https://mlsanity.com/paper/1611.08050/) (2016)
- [Generative Adversarial Text to Image Synthesis](https://mlsanity.com/paper/1605.05396/) (2016)
- [On Distillation of Guided Diffusion Models](https://mlsanity.com/paper/2210.03142/) (2022)
- [ModelScope Text-to-Video Technical Report](https://mlsanity.com/paper/2308.06571/) (2023)

## Built on by (most cited first, 30 of 35)

- [Arc2Face: A Foundation Model for ID-Consistent Human Faces](https://mlsanity.com/paper/2403.11641/) (2024)
- [MultiShotMaster: A Controllable Multi-Shot Video Generation Framework](https://mlsanity.com/paper/2512.03041/) (2025)
- [CharacterFactory: Sampling Consistent Characters with GANs for Diffusion Models](https://mlsanity.com/paper/2404.15677/) (2024)
- [FastVMT: Eliminating Redundancy in Video Motion Transfer](https://mlsanity.com/paper/2602.05551/) (2026)
- [Personalized Image Generation with Deep Generative Models: A Decade Survey](https://mlsanity.com/paper/2502.13081/) (2025)
- [WithAnyone: Towards Controllable and ID Consistent Image Generation](https://mlsanity.com/paper/2510.14975/) (2025)
- [Arc2Avatar: Generating Expressive 3D Avatars from a Single Image via ID Guidance](https://mlsanity.com/paper/2501.05379/) (2025)
- [CoRe: Context-Regularized Text Embedding Learning for Text-to-Image Personalization](https://mlsanity.com/paper/2408.15914/) (2024)
- [Data Synthesis with Diverse Styles for Face Recognition via 3DMM-Guided Diffusion](https://mlsanity.com/paper/2504.00430/) (2025)
- [VFXMaster: Unlocking Dynamic Visual Effect Generation via In-Context Learning](https://mlsanity.com/paper/2510.25772/) (2025)
- [MoTrans: Customized Motion Transfer with Text-driven Video Diffusion Models](https://mlsanity.com/paper/2412.01343/) (2024)
- [AttnDreamBooth: Towards Text-Aligned Personalized Text-to-Image Generation](https://mlsanity.com/paper/2406.05000/) (2024)
- [Deepfake Media Generation and Detection in the Generative AI Era: A Survey and Outlook](https://mlsanity.com/paper/2411.19537/) (2024)
- [SHMT: Self-supervised Hierarchical Makeup Transfer via Latent Diffusion Models](https://mlsanity.com/paper/2412.11058/) (2024)
- [DynamicID: Zero-Shot Multi-ID Image Personalization with Flexible Facial Editability](https://mlsanity.com/paper/2503.06505/) (2025)
- [ReNeg: Learning Negative Embedding with Reward Guidance](https://mlsanity.com/paper/2412.19637/) (2024)
- [IdentityStory: Taming Your Identity-Preserving Generator for Human-Centric Story Generation](https://mlsanity.com/paper/2512.23519/) (2025)
- [LoopAnimate: Loopable Salient Object Animation](https://mlsanity.com/paper/2404.09172/) (2024)
- [DynASyn: Multi-Subject Personalization Enabling Dynamic Action Synthesis](https://mlsanity.com/paper/2503.17728/) (2025)
- [Dense-Face: Personalized Face Generation Model via Dense Annotation Prediction](https://mlsanity.com/paper/2412.18149/) (2024)
- [MasterWeaver: Taming Editability and Face Identity for Personalized Text-to-Image Generation](https://mlsanity.com/paper/2405.05806/) (2024)
- [AnyLogo: Symbiotic Subject-Driven Diffusion System with Gemini Status](https://mlsanity.com/paper/2409.17740/) (2024)
- [Teleportraits: Training-Free People Insertion into Any Scene](https://mlsanity.com/paper/2510.05660/) (2025)
- [RealisID: Scale-Robust and Fine-Controllable Identity Customization via Local and Global Complementation](https://mlsanity.com/paper/2412.16832/) (2024)
- [RefSTAR: Blind Facial Image Restoration with Reference Selection, Transfer, and Reconstruction](https://mlsanity.com/paper/2507.10470/) (2025)
- [StructDiff: A Structure-Preserving and Spatially Controllable Diffusion Model for Single-Image Generation](https://mlsanity.com/paper/2604.12575/) (2026)
- ["I Know It When I See It": Mood Spaces for Connecting and Expressing Visual Concepts](https://mlsanity.com/paper/2504.15145/) (2025)
- [StyleYourSmile: Cross-Domain Face Retargeting Without Paired Multi-Style Data](https://mlsanity.com/paper/2512.01895/) (2025)
- [Training for Identity, Inference for Controllability: A Unified Approach to Tuning-Free Face Personalization](https://mlsanity.com/paper/2512.03964/) (2025)
- [Video2LoRA: Unified Semantic-Controlled Video Generation via Per-Reference-Video LoRA](https://mlsanity.com/paper/2603.08210/) (2026)

## Abstract (arXiv)

Recent advances in large pretrained text-to-image models have shown unprecedented capabilities for high-quality human-centric generation, however, customizing face identity is still an intractable problem. Existing methods cannot ensure stable identity preservation and flexible editability, even with several images for each subject during training. In this work, we propose StableIdentity, which allows identity-consistent recontextualization with just one face image. More specifically, we employ a face encoder with an identity prior to encode the input face, and then land the face representation into a space with an editable prior, which is constructed from celeb names. By incorporating identity prior and editability prior, the learned identity can be injected anywhere with various contexts. In addition, we design a masked two-phase diffusion loss to boost the pixel-level perception of the input face and maintain the diversity of generation. Extensive experiments demonstrate our method outperforms previous customization methods. In addition, the learned identity can be flexibly combined with the off-the-shelf modules such as ControlNet. Notably, to the best knowledge, we are the first to directly inject the identity learned from a single image into video/3D generation without finetuning. We believe that the proposed StableIdentity is an important step to unify image, video, and 3D customized generation models.