The Institute for Visualization and Interactive Systems (VIS) at the University of Stuttgart is an institute of the department of computer science in the faculty of computer science, electrical engineering and information technology. Around 70 people are conducting research and teaching in the areas of visualisation and computer graphics, human-computer interaction and cognitive systems, computer vision and pattern recognition as well as augmented and virtual reality. This DataVerse contains the research data produced by the institute in these fields. Large-scale projects – like collaborative research centres – the institute is participating in might have additional DataVerses containing data produced at VIS. Furthermore, we recommend also visiting the DataVerse of VISUS, our closely related central research institute for the area of visualisation.
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1 to 10 of 10,015 Results
VQA-MHUG
Mar 3, 2025 - Collaborative Artificial Intelligence
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
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