PromptArtisan: Multi-instruction Image Editing in Single Pass with Complete Attention Control

Kunal Swami, Raghu Chittersu, Pranav Adlinge, Rajeev Irny, Shashavali Doodekula +1 more
2/14/2025
cs.CVcs.HC

No confident code implementation found for this paper. 3 possible matches can be shown below.

Abstract

We present PromptArtisan, a groundbreaking approach to multi-instruction image editing that achieves remarkable results in a single pass, eliminating the need for time-consuming iterative refinement. Our method empowers users to provide multiple editing instructions, each associated with a specific mask within the image. This flexibility allows for complex edits involving mask intersections or overlaps, enabling the realization of intricate and nuanced image transformations. PromptArtisan leverages a pre-trained InstructPix2Pix model in conjunction with a novel Complete Attention Control Mechanism (CACM). This mechanism ensures precise adherence to user instructions, granting fine-grained control over the editing process. Furthermore, our approach is zero-shot, requiring no additional training, and boasts improved processing complexity compared to traditional iterative methods. By seamlessly integrating multi-instruction capabilities, single-pass efficiency, and complete attention control, PromptArtisan unlocks new possibilities for creative and efficient image editing workflows, catering to both novice and expert users alike.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 3 weaker matches are hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{swami2025promptartisan,
  title  = {PromptArtisan: Multi-instruction Image Editing in Single Pass with Complete Attention Control},
  author = {Kunal Swami and Raghu Chittersu and Pranav Adlinge and Rajeev Irny and Shashavali Doodekula and Alok Shukla},
  year   = {2025},
  eprint = {2502.10258},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2502.10258v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2502.10258.svg)](https://codeofpaper.com/paper/2502.10258)

Discussion