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TallyQA Paper link

UPDATE: Code available at https://github.com/manoja328/tallyqacode

Please, download the dataset using this link. The zipped file contains json files for train and test respectively. Each entries in the dataset contains the following fields:

 {'answer': 4,
  'data_source': 'imported_genome',
  'image': 'VG_100K_2/2410408.jpg',
  'image_id': 92410408,
  'issimple': False,
  'question': 'How many headlights does the black bus have?',
  'question_id': 30095774}

Attributes such as answer, image-id, image ,question should be straighforward. The boolean flag field ( issimple) denotes whether the question is simple (True) or complex ( False) . The field 'data_source' shows the source of the question-answer pair. Questions collected from AMT annotators have data_source = amt and likewise for other sources. The images used in the dataset are derived from COCO and Visual Genome. The imported QA pairs have been derived from TDIUC and VQA datasets.

Please cite the work using the following Bibtex:

@inproceedings{acharya2019tallyqa,
  title={TallyQA: Answering Complex Counting Questions},
  author={Acharya, Manoj and Kafle, Kushal and Kanan, Christopher},
  booktitle={AAAI},
  year={2019}
}

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TallyQA: Answering Complex Counting Questions dataset

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