| --- |
| license: mit |
| pretty_name: TextEraseBench |
| task_categories: |
| - image-to-image |
| tags: |
| - text-removal |
| - object-removal |
| - image-inpainting |
| - mask-conditioned-editing |
| - osor |
| --- |
| |
| # TextEraseBench |
|
|
| TextEraseBench is a text-removal benchmark for evaluating object removal and inpainting methods on text overlays and scene text-like objects. |
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| Dataset page: https://huggingface.co/datasets/QinmingZhou/TextEraseBench |
|
|
| ## Dataset Summary |
|
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| TextEraseBench contains 185 paired samples. Each sample includes an input image containing target text, a paired clean background, and a removal mask. The benchmark is designed to test whether methods can remove text while preserving the surrounding background structure. |
|
|
| ## Dataset Structure |
|
|
| ```text |
| TextEraseBench/ |
| ├── shot/ # text-present input images |
| ├── bg/ # paired clean background images |
| └── mask/ # target text/effect masks |
| ``` |
|
|
| For each sample id `<stem>`: |
|
|
| ```text |
| shot/<stem>.png |
| bg/<stem>.png |
| mask/<stem>.png |
| ``` |
|
|
| ## Usage |
|
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| Use `shot` as the input image, `mask` as the removal condition, and `bg` as the paired target for evaluation. |
|
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| ## Dataset Creation |
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| TextEraseBench is constructed through a manual-to-automated pipeline. Target text regions are manually annotated with fine-grained bounding boxes, then removed to create paired clean backgrounds. Samples undergo secondary verification to filter artifacts and semantic inconsistencies. |
|
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| ## Intended Use |
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| TextEraseBench is intended for evaluating text removal, object removal, and image inpainting models on paired-background examples. |
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|
