metadata
license: creativeml-openrail-m
configs:
- config_name: default
data_files:
- split: synth
path: data/synth-*
- split: real
path: data/real-*
dataset_info:
features:
- name: id
dtype: int32
- name: original_image
dtype: image
- name: partedit
dtype: image
- name: subject
dtype: string
- name: edit
dtype: string
- name: part
dtype: string
- name: gt_mask
dtype: image
- name: class_name
dtype: string
- name: prompt_original
dtype: string
- name: prompt_changed
dtype: string
- name: p2p_prompt
dtype: string
- name: p2p_template
dtype: string
- name: instructp2p_edit1
dtype: string
- name: instructp2p_edit2
dtype: string
- name: instructp2p_edit3
dtype: string
- name: seed
dtype: int32
splits:
- name: synth
num_bytes: 159677179
num_examples: 60
- name: real
num_bytes: 9967718
num_examples: 13
download_size: 169623238
dataset_size: 169644897
task_categories:
- text-to-image
- image-to-image
language:
- en
tags:
- Part Editing
- image
- Editing
size_categories:
- n<1K
arxiv: 2502.0405
pretty_name: PartEdit
Dataset Card for Dataset Name
This benchmark is part of PartEdit: Fine-Grained Image Editing using Pre-Trained Diffusion Models accepted in Siggraph 2025.
Dataset Details
Dataset Description
Small benchmark of part editing.
- Curated by: Authors
- Funded by [optional]: KAUST
- Shared by [optional]: Authors
- Language(s) (NLP): EN
- License: creativeml-openrail-m
Dataset Sources [optional]
- Repository: https://gorluxor.github.io/part-edit/
- Paper [optional]: https://arxiv.org/abs/2502.04050
- Demo [optional]: https://gorluxor.github.io/part-edit/
Annotation process
Using https://www.makesense.ai/ to annotate ground truth regions.
Bias, Risks, and Limitations
The generated images might contain biases from the underlying models.
Recommendations
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
Citation
BibTeX:
@inproceedings{cvejic2025partedit,
title={PartEdit: Fine-Grained Image Editing using Pre-Trained Diffusion Models},
author={Cvejic, Aleksandar and Eldesokey, Abdelrahman and Wonka, Peter},
booktitle={Proceedings of the Special Interest Group on Computer Graphics and Interactive Techniques Conference Conference Papers},
pages={1--11},
year={2025}
}
APA:
Cvejic, A., Eldesokey, A., & Wonka, P. (2025, August). PartEdit: Fine-Grained Image Editing using Pre-Trained Diffusion Models. In Proceedings of the Special Interest Group on Computer Graphics and Interactive Techniques Conference Conference Papers (pp. 1-11).