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Code release for our TACL paper "Overcoming Source Object Grounding for Semantic Image Editing"

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R-SIE

This repo provides the official code of TACL paper: Overcoming Source Object Grounding for Semantic Image Editing

Official implementation (PyTorch + diffusers) of
“Overcoming Source-Object Grounding for Semantic Image Editing”
accepted to TACL (2025).
We introduce a Region-wise Diffusion Process (RwDP) that cleanly separates background reconstruction from object manipulation, eliminating the grounding errors that plague prior SIE pipelines.

📦 Repository layout

r-sie/
├─ src/                # source codes
│   └─ RwDP_pipeline.py     # huggingface diffusers pipeline for region-wise diffusion process
└─ README.md

Planned additions

  • code for data generation process – automatic triplet generation (code & instructions) 🚧
  • test_sets/ – links to the cleaned evaluation splits 🚧
  • requirements – required packages to run codes 🚧

🔧 Prerequisites

package tested version
Python 3.9
PyTorch 1.12
diffusers 0.22.0
transformers 4.36.2
accelerate 0.27.2

📄 License

Code is released under the MIT License; see LICENSE. Model checkpoints follow the original Stable Diffusion v1.5 CreativeML license.


🙋 Questions & Contact

Open an issue or e-mail y970120@snu.ac.kr. We welcome pull requests for bug-fixes or documentation!

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Code release for our TACL paper "Overcoming Source Object Grounding for Semantic Image Editing"

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