Collaborative Artificial Intelligence

Group headed by Andreas Bulling of the Human-Computer Interaction and Cognitive Systems department of the University of Stuttgart.

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11 to 20 of 1,117 Results

difficulty_scores.pickle Oct 28, 2024 - VQA-MHUG Unknown - 78.0 KB - MD5: d24af997f7d7583dfe36b5ecc3ba5d96 [pickled pandas dataframe] difficulty scores calculated for all question-image pairs
generate_deliverables.py Oct 28, 2024 - VQA-MHUG Python Source Code - 7.8 KB - MD5: 3b05d7b4d9d4baa17b84ad27ccef146c script to generate fixation maps and scanpaths from fixation data
reasoning_types.pickle Oct 28, 2024 - VQA-MHUG Unknown - 97.8 KB - MD5: 3f139187c1914e9385c784b3cab890e9 [pickled pandas dataframe] reasoning type for all question-image pairs
vqa-mhug_answers.pickle Oct 28, 2024 - VQA-MHUG Unknown - 261.8 KB - MD5: fb4e3673787c5e2d4de73ee03b0171ef [pickled pandas dataframe] [VQA stimuli] [sequential presentation] participant answers to VQA question after viewing both stimuli
vqa-mhug_bboxes.pickle Oct 28, 2024 - VQA-MHUG Unknown - 1.5 MB - MD5: 02724ac0685c3d0edb905eeafe03b94e [pickled pandas dataframe] [VQA stimuli] [sequential presentation] bounding box coordinates of text (words) and image
vqa-mhug_gaze.pickle Oct 28, 2024 - VQA-MHUG Unknown - 54.0 MB - MD5: 211f7a3d94500d907cec79069d05000a [pickled pandas dataframe] [VQA stimuli] [sequential presentation] fixation data of both eyes on both stimuli
vqa-mhug-jr_answers.pickle Oct 28, 2024 - VQA-MHUG Unknown - 94.2 KB - MD5: e91c530e707cc7bd93d97ad03c2b046a [pickled pandas dataframe] [VQA stimuli] [joint presentation] participant answers to VQA question after viewing joint stimulus
vqa-mhug-jr_bboxes.pickle Oct 28, 2024 - VQA-MHUG Unknown - 426.8 KB - MD5: 817a7f9dfea962c8534d5c292cdd917f [pickled pandas dataframe] [VQA stimuli] [joint presentation] bounding box coordinates of text (words) and image
vqa-mhug-jr_gaze.pickle Oct 28, 2024 - VQA-MHUG Unknown - 12.2 MB - MD5: 81216e1ca95c0617367fb891e419feca [pickled pandas dataframe] [VQA stimuli] [sequential presentation] fixation data of both eyes on joint stimulus
InteRead May 22, 2024 Zermiani, Francesca, 2024, "InteRead", https://doi.org/10.18419/DARUS-4091, DaRUS, V1, UNF:6:peWc+ExRsnPhsVEeOyMu0w== [fileUNF] The InteRead dataset is designed to explore the impact of interruptions on reading behavior. It includes eye-tracking data from 50 adults with normal or corrected-to-normal eyesight and proficiency in English (native or C1 level). The dataset encompasses a self-paced reading task of an English fictional text, with participants encountering interrup...

difficulty_scores.pickle

Oct 28, 2024 - VQA-MHUG

Unknown - 78.0 KB -

[pickled pandas dataframe] difficulty scores calculated for all question-image pairs

generate_deliverables.py

Oct 28, 2024 - VQA-MHUG

Python Source Code - 7.8 KB -

script to generate fixation maps and scanpaths from fixation data

reasoning_types.pickle

Oct 28, 2024 - VQA-MHUG

Unknown - 97.8 KB -

[pickled pandas dataframe] reasoning type for all question-image pairs

vqa-mhug_answers.pickle

Oct 28, 2024 - VQA-MHUG

Unknown - 261.8 KB -

[pickled pandas dataframe] [VQA stimuli] [sequential presentation] participant answers to VQA question after viewing both stimuli

vqa-mhug_bboxes.pickle

Oct 28, 2024 - VQA-MHUG

Unknown - 1.5 MB -

[pickled pandas dataframe] [VQA stimuli] [sequential presentation] bounding box coordinates of text (words) and image

vqa-mhug_gaze.pickle

Oct 28, 2024 - VQA-MHUG

Unknown - 54.0 MB -

[pickled pandas dataframe] [VQA stimuli] [sequential presentation] fixation data of both eyes on both stimuli

vqa-mhug-jr_answers.pickle

Oct 28, 2024 - VQA-MHUG

Unknown - 94.2 KB -

[pickled pandas dataframe] [VQA stimuli] [joint presentation] participant answers to VQA question after viewing joint stimulus

vqa-mhug-jr_bboxes.pickle

Oct 28, 2024 - VQA-MHUG

Unknown - 426.8 KB -

[pickled pandas dataframe] [VQA stimuli] [joint presentation] bounding box coordinates of text (words) and image

vqa-mhug-jr_gaze.pickle

Oct 28, 2024 - VQA-MHUG

Unknown - 12.2 MB -

[pickled pandas dataframe] [VQA stimuli] [sequential presentation] fixation data of both eyes on joint stimulus

InteRead

May 22, 2024

Zermiani, Francesca, 2024, "InteRead", https://doi.org/10.18419/DARUS-4091, DaRUS, V1, UNF:6:peWc+ExRsnPhsVEeOyMu0w== [fileUNF]

The InteRead dataset is designed to explore the impact of interruptions on reading behavior. It includes eye-tracking data from 50 adults with normal or corrected-to-normal eyesight and proficiency in English (native or C1 level). The dataset encompasses a self-paced reading task of an English fictional text, with participants encountering interrup...

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