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| license: cc-by-4.0 |
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| # VistaQA: Benchmarking Joint Visual Question Answering and Pixel-Level Evidence |
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| ## Overview |
| VistaQA is a benchmark for the joint evaluation of free-form answer correctness and pixel-level visual evidence alignment in visual question answering. It contains 1,157 expert-curated samples across six task types and six visual domains, spanning perception to compositional and relational reasoning. Each sample requires both a textual answer and corresponding segmentation masks that support the prediction. The benchmark also includes hallucination-aware samples in which no valid visual evidence exists. |
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| ## Dataset Structure |
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|
| ``` |
| VistaQA/ |
| ├── 1.jpg |
| ├── 1.json |
| ├── 2.jpg |
| ├── 2.json |
| └── ... |
| ``` |
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| Each image file (`.jpg` or `.png`) is paired with a corresponding `.json` file sharing the same file ID. |
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| ## Annotation Format (Example) |
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| ```json |
| { |
| "image": { |
| "image_id": 979, |
| "width": 1500, |
| "height": 2060, |
| "file_name": "979.jpg" |
| }, |
| "question": "how many windows on the building are not partially occluded by the balusters?", |
| "answer": "there are 13 windows that not partially occluded by the balusters.", |
| "task_type": "counting", |
| "task_domain": "outdoor", |
| "num_instances": 13, |
| "hallucination": 0, |
| "annotations": [ |
| { |
| "id": 523353741, |
| "segmentation": { |
| "size": [ |
| 2060, |
| 1500 |
| ], |
| "counts": "l][T1n0g4TOPe1e6I6M3N10000O2O0000000000000O100001O00000000000000000000000000000000000000000000000001O0000000000O1000000001O0000O2O00000000000001O0O1000000000O101O0001O00O1000O1001N10000O1O100O1O1O1O1O1N2O1O1O1_N^VNXLbi1f3cVNVL^i1i3gVNRLZi1m3SWNfKoh1X4TWNfKlh15ZVNV3k0dLmh1OdVNV3`0kLmh1JoVNR35SMQi1BZWNo2F^Mjj14VTN]1Q1^Nmj1OZTNHKV1P1SOoj1IjTNl0;ZO\\l1:hSNE`n1O2Lcejb1" |
| }, |
| "bbox": [ |
| 578.0, |
| 636.0, |
| 112.0, |
| 228.0 |
| ], |
| "area": 23791 |
| } |
| ] |
| } |
| |
| |
| ``` |
| Note: For brevity, only one of the 13 masks is shown. |
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| ### Field Descriptions |
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| - **image**: Filename of the associated image and its metadata (e.g., width, height) |
| - **question**: Visual question answering (VQA) |
| - **answer**: Ground-truth answer (free-form) |
| - **task_type**: Type of reasoning (attribute, identification, OCR, counting, spatial, comparison) |
| - **task_domain**: Domain category (AV, indoor, outdoor, robotics, math, science) |
| - **num_instances**: Number of instances for visual evidence masks |
| - **hallucination**: Indicates whether valid visual evidence exists (0 = evidence present, 1 = no valid evidence) |
| - **annotations**: Segmentation mask(s) representing supporting evidence |
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