| --- |
| task_categories: |
| - image-to-text |
| dataset_info: |
| features: |
| - name: id |
| dtype: string |
| - name: image_1 |
| dtype: image |
| - name: image_2 |
| dtype: image |
| - name: choices |
| struct: |
| - name: A |
| dtype: string |
| - name: B |
| dtype: string |
| - name: C |
| dtype: string |
| - name: D |
| dtype: string |
| - name: ground_truth |
| dtype: string |
| - name: category |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 4188405701.612 |
| num_examples: 1756 |
| download_size: 5002312163 |
| dataset_size: 4188405701.612 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| --- |
| |
| # VDiff-Bench |
|
|
| [Paper](https://huggingface.co/papers/2609.06245) | [Project page](https://huggingface.co/spaces/elaine1wan/vdiff-bench) |
|
|
| VDiff-Bench is a multiple-choice benchmark for fine-grained visual difference identification. Each example presents two similar images and four candidate descriptions, exactly one of which states a real difference between the images. |
|
|
| ## Dataset structure |
|
|
| The `train` split contains 1,756 questions with the following fields: |
|
|
| - `id`: stable example identifier. |
| - `image_1`, `image_2`: the paired images. |
| - `choices`: an object containing answer choices `A`, `B`, `C`, and `D`. |
| - `ground_truth`: label of the correct choice. |
| - `category`: visual change category. |
|
|
| The public release intentionally excludes source identifiers, intermediate difference annotations, generated-negative metadata, and other dataset-construction fields. |
|
|
| ## Change categories |
|
|
| | Category | Questions | |
| |---|---:| |
| | Change of position | 158 | |
| | Change of motion | 138 | |
| | Change of color (regional) | 170 | |
| | Change of color (whole image) | 147 | |
| | Appear / disappear | 201 | |
| | Change of noise / resolution | 150 | |
| | Change of texture | 177 | |
| | Substitution and size | 199 | |
| | OCR | 221 | |
| | Illumination | 195 | |
|
|
| ## Loading |
|
|
| ```python |
| from datasets import load_dataset |
| |
| dataset = load_dataset("elaine1wan/image_diff_data", split="train") |
| example = dataset[0] |
| ``` |
|
|
| `image_1` and `image_2` are decoded as PIL images by default. Benchmark performance is measured using exact-match accuracy on `ground_truth`. |
|
|
| ## Citation |
|
|
| Citation information will be added with the accompanying paper release. |
