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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1 to 10 of 1,117 Results

VQA-MHUG Mar 3, 2025 Sood, Ekta; Kögel, Fabian; Bulling, Andreas, 2024, "VQA-MHUG", https://doi.org/10.18419/DARUS-4428, DaRUS, V2 We present VQA-MHUG - a novel 49-participant dataset of multimodal human gaze on both images and questions during visual question answering (VQA), collected using a high-speed eye tracker. To the best of our knowledge, this is the first resource containing multimodal human gaze data over a textual question and the corresponding image. Our corpus en...
README.md Mar 3, 2025 - VQA-MHUG Markdown Text - 4.2 KB - MD5: b8367a799da2dbfbb26a6ec4ebc67a5b Dataset information and usage description
SalChartQA: Question-driven Saliency on Information Visualisations (Dataset and Reproduction Data) Nov 22, 2024 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations" Wang, Yao, 2024, "SalChartQA: Question-driven Saliency on Information Visualisations (Dataset and Reproduction Data)", https://doi.org/10.18419/DARUS-3884, DaRUS, V2 Understanding the link between visual attention and user’s needs when visually exploring information visualisations is under-explored due to a lack of large and diverse datasets to facilitate these analyses. To fill this gap, we introduce SalChartQA - a novel crowd-sourced dataset that uses the BubbleView interface as a proxy for human gaze and a q...
SalChartQA-npy.zip Nov 22, 2024 - SalChartQA: Question-driven Saliency on Information Visualisations (Dataset and Reproduction Data) ZIP Archive - 730.9 MB - MD5: aecb5a6a4029bcadb4fe1b0ff78a6345 npy files for dataloader
air-mhug_answers.pickle Oct 28, 2024 - VQA-MHUG Unknown - 60.8 KB - MD5: 1cc24a7c924c3a46b44546f983ac7c79 [pickled pandas dataframe] [AiR stimuli] [sequential presentation] participant answers to VQA question after viewing both stimuli
air-mhug_bboxes.pickle Oct 28, 2024 - VQA-MHUG Unknown - 128.5 KB - MD5: 3a5462b2f96d6b0a4b0ad9ac0c595d5f [pickled pandas dataframe] [AiR stimuli] [sequential presentation] bounding box coordinates of text (words) and image
air-mhug_gaze.pickle Oct 28, 2024 - VQA-MHUG Unknown - 4.7 MB - MD5: b72e6f16af7c4be11138db20927f5d64 [pickled pandas dataframe] [AiR stimuli] [sequential presentation] fixation data of both eyes on both stimuli
air-mhug-jr_answers.pickle Oct 28, 2024 - VQA-MHUG Unknown - 58.6 KB - MD5: c0d9f958466c90843b9115fff873aef6 [pickled pandas dataframe] [AiR stimuli] [joint presentation] participant answers to VQA question after viewing joint stimulus
air-mhug-jr_bboxes.pickle Oct 28, 2024 - VQA-MHUG Unknown - 88.8 KB - MD5: fede2879e467f90ae38975dc1dd0ea63 [pickled pandas dataframe] [AiR stimuli] [joint presentation] bounding box coordinates of text (words) and image
air-mhug-jr_gaze.pickle Oct 28, 2024 - VQA-MHUG Unknown - 3.1 MB - MD5: 05d93d0152c9f418e7cd8c36a868712b [pickled pandas dataframe] [AiR stimuli] [joint presentation] fixation data of both eyes on joint stimulus

VQA-MHUG

Mar 3, 2025

Sood, Ekta; Kögel, Fabian; Bulling, Andreas, 2024, "VQA-MHUG", https://doi.org/10.18419/DARUS-4428, DaRUS, V2

We present VQA-MHUG - a novel 49-participant dataset of multimodal human gaze on both images and questions during visual question answering (VQA), collected using a high-speed eye tracker. To the best of our knowledge, this is the first resource containing multimodal human gaze data over a textual question and the corresponding image. Our corpus en...

README.md

Mar 3, 2025 - VQA-MHUG

Markdown Text - 4.2 KB -

Dataset information and usage description

SalChartQA: Question-driven Saliency on Information Visualisations (Dataset and Reproduction Data)

Nov 22, 2024 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations"

Wang, Yao, 2024, "SalChartQA: Question-driven Saliency on Information Visualisations (Dataset and Reproduction Data)", https://doi.org/10.18419/DARUS-3884, DaRUS, V2

Understanding the link between visual attention and user’s needs when visually exploring information visualisations is under-explored due to a lack of large and diverse datasets to facilitate these analyses. To fill this gap, we introduce SalChartQA - a novel crowd-sourced dataset that uses the BubbleView interface as a proxy for human gaze and a q...

SalChartQA-npy.zip

Nov 22, 2024 - SalChartQA: Question-driven Saliency on Information Visualisations (Dataset and Reproduction Data)

ZIP Archive - 730.9 MB -

npy files for dataloader

air-mhug_answers.pickle

Oct 28, 2024 - VQA-MHUG

Unknown - 60.8 KB -

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

air-mhug_bboxes.pickle

Oct 28, 2024 - VQA-MHUG

Unknown - 128.5 KB -

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

air-mhug_gaze.pickle

Oct 28, 2024 - VQA-MHUG

Unknown - 4.7 MB -

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

air-mhug-jr_answers.pickle

Oct 28, 2024 - VQA-MHUG

Unknown - 58.6 KB -

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

air-mhug-jr_bboxes.pickle

Oct 28, 2024 - VQA-MHUG

Unknown - 88.8 KB -

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

air-mhug-jr_gaze.pickle

Oct 28, 2024 - VQA-MHUG

Unknown - 3.1 MB -

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

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