mlsanityData to 7 Oct 2026

Move and Act: Enhanced Object Manipulation and Background Integrity for Image Editing

arXiv 2407.17847 ↗First posted 25 Jul 2024cs.CVcited by 4

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Abstract (arXiv)

Current methods commonly utilize three-branch structures of inversion, reconstruction, and editing, to tackle consistent image editing task. However, these methods lack control over the generation position of the edited object and have issues with background preservation. To overcome these limitations, we propose a tuning-free method with only two branches: inversion and editing. This approach allows users to simultaneously edit the object's action and control the generation position of the edited object. Additionally, it achieves improved background preservation. Specifically, we transfer the edited object information to the target area and repair or preserve the background of other areas during the inversion process at a specific time step. In the editing stage, we use the image features in self-attention to query the key and value of the corresponding time step in the inversion to achieve consistent image editing. Impressive image editing results and quantitative evaluation demonstrate the effectiveness of our method. The code is available at https://github.com/mobiushy/move-act.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 24 of its 25 references that are in the map. First posted on arXiv 25 Jul 2024.

Builds on

24 of 25 references.

References · 24

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  3. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  4. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  5. 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,595
  6. 2022InstructPix2Pix: Learning to Follow Image Editing Instructionscited by 2,591
  7. 2022Prompt-to-Prompt Image Editing with Cross Attention Controlcited by 2,409
  8. 2022Imagic: Text-Based Real Image Editing with Diffusion Modelscited by 1,172
  9. 2022Null-text Inversion for Editing Real Images using Guided Diffusion Modelscited by 1,168
  10. 2022Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translationcited by 897
  11. 2023MasaCtrl: Tuning-Free Mutual Self-Attention Control for Consistent Image Synthesis and Editingcited by 722
  12. 2023Attend-and-Excite: Attention-Based Semantic Guidance for Text-to-Image Diffusion Modelscited by 696
12 more
  1. 2023Zero-shot Image-to-Image Translationcited by 503
  2. 2023Emergent Correspondence from Image Diffusioncited by 437
  3. 2023Training-Free Layout Control with Cross-Attention Guidancecited by 312
  4. 2023DragDiffusion: Harnessing Diffusion Models for Interactive Point-based Image Editingcited by 293
  5. 2023BoxDiff: Text-to-Image Synthesis with Training-Free Box-Constrained Diffusioncited by 280
  6. 2023Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifoldcited by 218
  7. 2023DragonDiffusion: Enabling Drag-style Manipulation on Diffusion Modelscited by 193
  8. 2023Grounded Text-to-Image Synthesis with Attention Refocusingcited by 163
  9. 2023Prompt Tuning Inversion for Text-Driven Image Editing Using Diffusion Modelscited by 98
  10. 2023Real-Time Flying Object Detection with YOLOv8cited by 93
  11. 2023Freestyle Layout-to-Image Synthesiscited by 67
  12. 2023KV Inversion: KV Embeddings Learning for Text-Conditioned Real Image Action Editingcited by 21

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 2.

4 papers.