| --- |
| language: |
| - en |
| - zh |
| pretty_name: Inter-Edit-Train |
| size_categories: |
| - 1M<n<10M |
| task_categories: |
| - image-to-image |
| tags: |
| - image-editing |
| - benchmark |
| - computer-vision |
| - multimodal |
| --- |
| |
| # Inter-Edit-Train |
|
|
| Inter-Edit-Train is the official large-scale training set released for the CVPR 2026 paper **Inter-Edit: First Benchmark for Interactive Instruction-Based Image Editing**. |
|
|
| This dataset is designed for the Interactive Instruction-based Image Editing (I^3E) task, where a model performs localized image edits from a concise textual instruction together with imprecise spatial guidance. |
|
|
| ## Highlights |
|
|
| - **1,099,964** image editing pairs |
| - **610,186** unique source images |
| - Four edit types: **Local**, **Add**, **Remove**, and **Texture** |
| - Seven common aspect ratios from **16:9** to **9:16** |
| - Includes edit instructions, masks, bounding boxes, and an extra `better_data` flag |
| - All release filenames are anonymized with index-based names; original internal filenames are not exposed in the packaged archives |
|
|
| ## Relation to the paper |
|
|
| This release corresponds to the training split described in the paper. The released manifest keeps the fields needed for training and data usage: |
|
|
| - `instruction` |
| - `edit_type` |
| - `bounding_box` |
| - `bbox_reference_dimensions` |
| - `better_data` |
| - anonymized source / target / mask asset locations |
|
|
| The key `better_data` is **not** a paper-defined benchmark field. It is an additional release-only flag indicating samples that were judged to be more suitable for training after filtering. |
|
|
| ## Data layout |
|
|
| Because the full training set is extremely large, the assets are released as sharded tar archives: |
|
|
| - `source_shards/source-xxxxx-of-xxxxx.tar` |
| - `asset_shards/asset-xxxxx-of-xxxxx.tar` |
| - `metadata/train-xxxxx-of-xxxxx.jsonl.gz` |
|
|
| Each asset name inside the tar archives is anonymized: |
|
|
| - source image: `sources/source_0000000.png` |
| - edited image: `targets/target_0000000.png` |
| - mask image: `masks/mask_0000000.png` |
|
|
| Each metadata row records which tar shard and which internal filename should be used for that sample. |
|
|
| ## Metadata schema |
|
|
| Each JSONL record contains: |
|
|
| - `sample_id`: zero-based sample index |
| - `source_id`: zero-based unique source-image index |
| - `edit_type` |
| - `instruction` |
| - `better_data` |
| - `bounding_box` |
| - `bbox_reference_dimensions` |
| - `source_archive` |
| - `source_file` |
| - `asset_archive` |
| - `target_file` |
| - `mask_file` |
|
|
| ## Example metadata entry |
|
|
| ```json |
| { |
| "sample_id": 0, |
| "source_id": 0, |
| "edit_type": "Add", |
| "instruction": "添加一双发光的筷子", |
| "better_data": false, |
| "bounding_box": [357, 694, 902, 926], |
| "bbox_reference_dimensions": {"width": 960, "height": 960}, |
| "source_archive": "source_shards/source-00000-of-00245.tar", |
| "source_file": "sources/source_0000000.png", |
| "asset_archive": "asset_shards/asset-00000-of-00275.tar", |
| "target_file": "targets/target_0000000.png", |
| "mask_file": "masks/mask_0000000.png" |
| } |
| ``` |
|
|
| ## Usage notes |
|
|
| - This is the **training** release, not the manually annotated test benchmark. |
| - The canonical sample order follows the original `Inter-Edit-train.json`. |
| - Source images are deduplicated globally and indexed separately from sample indices. |
| - Asset filenames are anonymized by design. |
|
|
| ## Citation |
|
|
| If you use this dataset, please cite: |
|
|
| ```bibtex |
| @inproceedings{liu2026interedit, |
| title={Inter-Edit: First Benchmark for Interactive Instruction-Based Image Editing}, |
| author={Liu, Delong and Hou, Haotian and Hou, Zhaohui and Huang, Zhiyuan and Han, Shihao and Zhan, Mingjie and Zhao, Zhicheng and Su, Fei}, |
| booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, |
| year={2026} |
| } |
| ``` |
|
|
