# MagicQuill: An Intelligent Interactive Image Editing System

arXiv: https://arxiv.org/abs/2411.09703 · HTML: https://mlsanity.com/paper/2411.09703/

## Key facts

- Cited by 30 papers in the map (data through 14 Oct 2026).
- Builds on 72 of its 85 references that are in the map.
- First posted on arXiv 14 Nov 2024.

## Builds on (most cited first, 30 of 72)

- [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)
- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [High-Resolution Image Synthesis with Latent Diffusion Models](https://mlsanity.com/paper/2112.10752/) (2021)
- [GPT-4 Technical Report](https://mlsanity.com/paper/2303.08774/) (2023)
- [LoRA: Low-Rank Adaptation of Large Language Models](https://mlsanity.com/paper/2106.09685/) (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)
- [Visual Instruction Tuning](https://mlsanity.com/paper/2304.08485/) (2023)
- [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)
- [GPT-4o System Card](https://mlsanity.com/paper/2410.21276/) (2024)
- [Improved Baselines with Visual Instruction Tuning](https://mlsanity.com/paper/2310.03744/) (2023)
- [SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis](https://mlsanity.com/paper/2307.01952/) (2023)
- [LAION-5B: An open large-scale dataset for training next generation image-text models](https://mlsanity.com/paper/2210.08402/) (2022)
- [Elucidating the Design Space of Diffusion-Based Generative Models](https://mlsanity.com/paper/2206.00364/) (2022)
- [InstructPix2Pix: Learning to Follow Image Editing Instructions](https://mlsanity.com/paper/2211.09800/) (2022)
- [VQA: Visual Question Answering](https://mlsanity.com/paper/1505.00468/) (2015)
- [SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations](https://mlsanity.com/paper/2108.01073/) (2021)
- [Imagic: Text-Based Real Image Editing with Diffusion Models](https://mlsanity.com/paper/2210.09276/) (2022)
- [MagicBrush: A Manually Annotated Dataset for Instruction-Guided Image Editing](https://mlsanity.com/paper/2306.10012/) (2023)
- [Generative Multimodal Models are In-Context Learners](https://mlsanity.com/paper/2312.13286/) (2023)
- [AnyDoor: Zero-shot Object-level Image Customization](https://mlsanity.com/paper/2307.09481/) (2023)
- [OmniGen: Unified Image Generation](https://mlsanity.com/paper/2409.11340/) (2024)
- [SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation](https://mlsanity.com/paper/2404.14396/) (2024)
- [Emu Edit: Precise Image Editing via Recognition and Generation Tasks](https://mlsanity.com/paper/2311.10089/) (2023)
- [Diffusion Self-Guidance for Controllable Image Generation](https://mlsanity.com/paper/2306.00986/) (2023)
- [DreamLLM: Synergistic Multimodal Comprehension and Creation](https://mlsanity.com/paper/2309.11499/) (2023)
- [Generating Images with Multimodal Language Models](https://mlsanity.com/paper/2305.17216/) (2023)
- [Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMs](https://mlsanity.com/paper/2401.11708/) (2024)

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

- [OmniGuard: Hybrid Manipulation Localization via Augmented Versatile Deep Image Watermarking](https://mlsanity.com/paper/2412.01615/) (2024)
- [BrushEdit: All-In-One Image Inpainting and Editing](https://mlsanity.com/paper/2412.10316/) (2024)
- [ContextFlow: Training-Free Video Object Editing via Adaptive Context Enrichment](https://mlsanity.com/paper/2509.17818/) (2025)
- [MangaNinja: Line Art Colorization with Precise Reference Following](https://mlsanity.com/paper/2501.08332/) (2025)
- [Hallucination at a Glance: Controlled Visual Edits and Fine-Grained Multimodal Learning](https://mlsanity.com/paper/2506.07227/) (2025)
- [LMMs Meet Object-Centric Vision: Understanding, Segmentation, Editing and Generation](https://mlsanity.com/paper/2604.11789/) (2026)
- [Trans-Adapter: A Plug-and-Play Framework for Transparent Image Inpainting](https://mlsanity.com/paper/2508.01098/) (2025)
- [SmartFreeEdit: Mask-Free Spatial-Aware Image Editing with Complex Instruction Understanding](https://mlsanity.com/paper/2504.12704/) (2025)
- [MIND-Edit: MLLM Insight-Driven Editing via Language-Vision Projection](https://mlsanity.com/paper/2505.19149/) (2025)
- [Neural-Driven Image Editing](https://mlsanity.com/paper/2507.05397/) (2025)
- [MagicQuillV2: Precise and Interactive Image Editing with Layered Visual Cues](https://mlsanity.com/paper/2512.03046/) (2025)
- [TP-Blend: Textual-Prompt Attention Pairing for Precise Object-Style Blending in Diffusion Models](https://mlsanity.com/paper/2601.08011/) (2026)
- [SPICE: A Synergistic, Precise, Iterative, and Customizable Image Editing Workflow](https://mlsanity.com/paper/2504.09697/) (2025)
- [Sketch3DVE: Sketch-based 3D-Aware Scene Video Editing](https://mlsanity.com/paper/2508.13797/) (2025)
- [DreamOmni3: Scribble-based Editing and Generation](https://mlsanity.com/paper/2512.22525/) (2025)
- [TextWand: A Unified Framework for Scene Text Editing](https://mlsanity.com/paper/2606.05730/) (2026)
- [ArtAug: Enhancing Text-to-Image Generation through Synthesis-Understanding Interaction](https://mlsanity.com/paper/2412.12888/) (2024)
- [ScribbleSense: Generative Scribble-Based Texture Editing with Intent Prediction](https://mlsanity.com/paper/2601.22455/) (2026)
- [EchoGen: Cycle-Consistent Learning for Unified Layout-Image Generation and Understanding](https://mlsanity.com/paper/2603.18001/) (2026)
- [Live Interactive Training for Video Segmentation](https://mlsanity.com/paper/2603.26929/) (2026)
- [Banana100: Breaking NR-IQA Metrics by 100 Iterative Image Replications with Nano Banana Pro](https://mlsanity.com/paper/2604.03400/) (2026)
- [TalkFashion: Intelligent Virtual Try-On Assistant Based on Multimodal Large Language Model](https://mlsanity.com/paper/2507.05790/) (2025)
- [PaintFlow: A Unified Framework for Interactive Oil Paintings Editing and Generation](https://mlsanity.com/paper/2512.08534/) (2025)
- [SketchAssist: A Practical Assistant for Semantic Edits and Precise Local Redrawing](https://mlsanity.com/paper/2512.14140/) (2025)
- [Design Generative AI for Practitioners: Exploring Interaction Approaches Aligned with Creative Practice](https://mlsanity.com/paper/2603.03074/) (2026)
- [Multi-Object Advertisement Creative Generation](https://mlsanity.com/paper/2603.13745/) (2026)
- [Redefining Quality Criteria and Distance-Aware Score Modeling for Image Editing Assessment](https://mlsanity.com/paper/2604.12175/) (2026)
- [SketchFaceGS: Real-Time Sketch-Driven Face Editing and Generation with Gaussian Splatting](https://mlsanity.com/paper/2604.19202/) (2026)
- [ScribbleEdit: Synthetic Data for Image Editing with Scribbles and Text](https://mlsanity.com/paper/2605.01135/) (2026)
- [RefGC-SR2: Reference-guided Super-Resolution and Refinement of AI Generated Content](https://mlsanity.com/paper/2606.15158/) (2026)

## Abstract (arXiv)

Image editing involves a variety of complex tasks and requires efficient and precise manipulation techniques. In this paper, we present MagicQuill, an integrated image editing system that enables swift actualization of creative ideas. Our system features a streamlined yet functionally robust interface, allowing for the articulation of editing operations (e.g., inserting elements, erasing objects, altering color) with minimal input. These interactions are monitored by a multimodal large language model (MLLM) to anticipate editing intentions in real time, bypassing the need for explicit prompt entry. Finally, we apply a powerful diffusion prior, enhanced by a carefully learned two-branch plug-in module, to process editing requests with precise control. Experimental results demonstrate the effectiveness of MagicQuill in achieving high-quality image edits. Please visit https://magic-quill.github.io to try out our system.