# UniEdit-Flow: Unleashing Inversion and Editing in the Era of Flow Models

arXiv: https://arxiv.org/abs/2504.13109 · HTML: https://mlsanity.com/paper/2504.13109/

## Key facts

- Cited by 39 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 83 of its 98 references that are in the map.
- First posted on arXiv 17 Apr 2025.

## 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 83)

- [Learning Transferable Visual Models From Natural Language Supervision](https://mlsanity.com/paper/2103.00020/) (2021)
- [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)
- [Hierarchical Text-Conditional Image Generation with CLIP Latents](https://mlsanity.com/paper/2204.06125/) (2022)
- [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)
- [Flow Matching for Generative Modeling](https://mlsanity.com/paper/2210.02747/) (2022)
- [Generative Adversarial Networks](https://mlsanity.com/paper/2203.00667/) (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)
- [Scaling Rectified Flow Transformers for High-Resolution Image Synthesis](https://mlsanity.com/paper/2403.03206/) (2024)
- [Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow](https://mlsanity.com/paper/2209.03003/) (2022)
- [DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation](https://mlsanity.com/paper/2208.12242/) (2022)
- [DreamFusion: Text-to-3D using 2D Diffusion](https://mlsanity.com/paper/2209.14988/) (2022)
- [InstructPix2Pix: Learning to Follow Image Editing Instructions](https://mlsanity.com/paper/2211.09800/) (2022)
- [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)
- [IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models](https://mlsanity.com/paper/2308.06721/) (2023)
- [Diffusion Posterior Sampling for General Noisy Inverse Problems](https://mlsanity.com/paper/2209.14687/) (2022)
- [LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop](https://mlsanity.com/paper/1506.03365/) (2015)
- [Null-text Inversion for Editing Real Images using Guided Diffusion Models](https://mlsanity.com/paper/2211.09794/) (2022)
- [The 2017 DAVIS Challenge on Video Object Segmentation](https://mlsanity.com/paper/1704.00675/) (2017)
- [Stochastic Interpolants: A Unifying Framework for Flows and Diffusions](https://mlsanity.com/paper/2303.08797/) (2023)
- [DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models](https://mlsanity.com/paper/2211.01095/) (2022)
- [Blended Diffusion for Text-driven Editing of Natural Images](https://mlsanity.com/paper/2111.14818/) (2021)
- [Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translation](https://mlsanity.com/paper/2211.12572/) (2022)
- [DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation](https://mlsanity.com/paper/2309.16653/) (2023)

## Built on by (most cited first, 30 of 39)

- [Exploring Multimodal Diffusion Transformers for Enhanced Prompt-based Image Editing](https://mlsanity.com/paper/2508.07519/) (2025)
- [SAEdit: Token-level control for continuous image editing via Sparse AutoEncoder](https://mlsanity.com/paper/2510.05081/) (2025)
- [AnchorFlow: Training-Free 3D Editing via Latent Anchor-Aligned Flows](https://mlsanity.com/paper/2511.22357/) (2025)
- [TrajFlow: Multi-modal Motion Prediction via Flow Matching](https://mlsanity.com/paper/2506.08541/) (2025)
- [Zero-Shot Dynamic Concept Personalization with Grid-Based LoRA](https://mlsanity.com/paper/2507.17963/) (2025)
- [ConsistEdit: Highly Consistent and Precise Training-free Visual Editing](https://mlsanity.com/paper/2510.17803/) (2025)
- [ProEdit: Inversion-based Editing From Prompts Done Right](https://mlsanity.com/paper/2512.22118/) (2025)
- [Object-WIPER : Training-Free Object and Associated Effect Removal in Videos](https://mlsanity.com/paper/2601.06391/) (2026)
- [Training-Free Text-Guided Color Editing with Multi-Modal Diffusion Transformer](https://mlsanity.com/paper/2508.09131/) (2025)
- [Improving Robotic Generalist Policies via Flow Reversal Steering](https://mlsanity.com/paper/2606.13675/) (2026)
- [DFVEdit: Conditional Delta Flow Vector for Zero-shot Video Editing](https://mlsanity.com/paper/2506.20967/) (2025)
- [LazyDrag: Enabling Stable Drag-Based Editing on Multi-Modal Diffusion Transformers via Explicit Correspondence](https://mlsanity.com/paper/2509.12203/) (2025)
- [SONIC: Spectral Optimization of Noise for Inpainting with Consistency](https://mlsanity.com/paper/2511.19985/) (2025)
- [LORE: Latent Optimization for Precise Semantic Control in Rectified Flow-based Image Editing](https://mlsanity.com/paper/2508.03144/) (2025)
- [FlowOpt: Fast Optimization Through Whole Flow Processes for Training-Free Editing](https://mlsanity.com/paper/2510.22010/) (2025)
- [SteerFlow: Steering Rectified Flows for Faithful Inversion-Based Image Editing](https://mlsanity.com/paper/2604.01715/) (2026)
- [The Devil is in Attention Sharing: Improving Complex Non-rigid Image Editing Faithfulness via Attention Synergy](https://mlsanity.com/paper/2512.14423/) (2025)
- [Free Lunch for Stabilizing Rectified Flow Inversion](https://mlsanity.com/paper/2602.11850/) (2026)
- [StreamEdit: Training-Free Video Editing via Few-Step Streaming Video Generation](https://mlsanity.com/paper/2605.21466/) (2026)
- [FlowSteer: Conditioning Flow Field for Consistent Image Restoration](https://mlsanity.com/paper/2512.08125/) (2025)
- [ContextDrag: Precise Drag-Based Image Editing via Context-Preserving Token Injection and Position-Aligned Attention](https://mlsanity.com/paper/2512.08477/) (2025)
- [Recolour What Matters: Region-Aware Colour Editing via Token-Level Diffusion](https://mlsanity.com/paper/2603.18466/) (2026)
- [AdaEdit: Adaptive Temporal and Channel Modulation for Flow-Based Image Editing](https://mlsanity.com/paper/2603.21615/) (2026)
- [Beyond Prompts: Unconditional 3D Inversion for Out-of-Distribution Shapes](https://mlsanity.com/paper/2604.14914/) (2026)
- [FlowAnchor: Stabilizing the Editing Signal for Inversion-Free Video Editing](https://mlsanity.com/paper/2604.22586/) (2026)
- [Dress-ED: Instruction-Guided Editing for Virtual Try-On and Try-Off](https://mlsanity.com/paper/2603.22607/) (2026)
- [3DPhysVideo: Consistency-Guided Flow SDE for Video Generation via 3D Scene Reconstruction and Physical Simulation](https://mlsanity.com/paper/2605.16795/) (2026)
- [Conditioning Matters: Stabilizing Inversion and Attention in Diffusion Image Editing](https://mlsanity.com/paper/2606.14125/) (2026)
- [Root-Selecting Fixed-Point Inversion for Rectified Flows via Trajectory Straightness](https://mlsanity.com/paper/2606.17584/) (2026)
- [h-Flow: Flexible Flow-based Image Editing via Doob's h-Transform](https://mlsanity.com/paper/2607.10800/) (2026)

## Abstract (arXiv)

Flow matching models have emerged as a strong alternative to diffusion models, but existing inversion and editing methods designed for diffusion are often ineffective or inapplicable to them. The straight-line, non-crossing trajectories of flow models pose challenges for diffusion-based approaches but also open avenues for novel solutions. In this paper, we introduce a predictor-corrector-based framework for inversion and editing in flow models. First, we propose Uni-Inv, an effective inversion method designed for accurate reconstruction. Building on this, we extend the concept of delayed injection to flow models and introduce Uni-Edit, a region-aware, robust image editing approach. Our methodology is tuning-free, model-agnostic, efficient, and effective, enabling diverse edits while ensuring strong preservation of edit-irrelevant regions. Extensive experiments across various generative models demonstrate the superiority and generalizability of Uni-Inv and Uni-Edit, even under low-cost settings. Project page: https://uniedit-flow.github.io/