SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations"

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1 to 10 of 663 Results

SalChartQA: Question-driven Saliency on Information Visualisations (Dataset and Reproduction Data) Nov 22, 2024 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
VisRecall++: Analysing and Predicting Recallability of Information Visualisations from Gaze Behaviour (Dataset and Reproduction Data) Apr 8, 2024 Wang, Yao; Bulling, Andreas, 2024, "VisRecall++: Analysing and Predicting Recallability of Information Visualisations from Gaze Behaviour (Dataset and Reproduction Data)", https://doi.org/10.18419/DARUS-3138, DaRUS, V1, UNF:6:NwphGtoYrBQqd2TyRh0OHA== [fileUNF] This dataset contains stimuli and collected participant data of VisRecall++. The structure of the dataset is described in the README-File. Further, if you are interested in related codes of the publication, you can find a copy of the code repository (see Metadata for Research Software) within this dataset.
Dataset.py Apr 8, 2024 - VisRecall++: Analysing and Predicting Recallability of Information Visualisations from Gaze Behaviour (Dataset and Reproduction Data) Python Source Code - 5.7 KB - MD5: bc554567b355511c4dadc543f9209a16
main.py Apr 8, 2024 - VisRecall++: Analysing and Predicting Recallability of Information Visualisations from Gaze Behaviour (Dataset and Reproduction Data) Python Source Code - 4.3 KB - MD5: 6dbc9847ff4b0d1c126a047f2c39d330
Model.py Apr 8, 2024 - VisRecall++: Analysing and Predicting Recallability of Information Visualisations from Gaze Behaviour (Dataset and Reproduction Data) Python Source Code - 2.0 KB - MD5: 9ec79413fcd39fd024d78aca990b11a5
README.md Apr 8, 2024 - VisRecall++: Analysing and Predicting Recallability of Information Visualisations from Gaze Behaviour (Dataset and Reproduction Data) Markdown Text - 1.6 KB - MD5: 7f5e4f3aa91c96da0dab17a722df928c
README.md Apr 8, 2024 - VisRecall++: Analysing and Predicting Recallability of Information Visualisations from Gaze Behaviour (Dataset and Reproduction Data) Markdown Text - 471 B - MD5: 6d5e28696c130c0c7d2ca4595e4483f1
split0_01_test.tab Apr 8, 2024 - VisRecall++: Analysing and Predicting Recallability of Information Visualisations from Gaze Behaviour (Dataset and Reproduction Data) Tabular Data - 1.3 MB - 8 Variables, 3000 Observations - UNF:6:MAoeMQ143uppJ/W6lUsOhg==
split0_01_train.tab Apr 8, 2024 - VisRecall++: Analysing and Predicting Recallability of Information Visualisations from Gaze Behaviour (Dataset and Reproduction Data) Tabular Data - 4.3 MB - 8 Variables, 9445 Observations - UNF:6:ERaGx3GYsw/WTGloE0ANNw==

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

Nov 22, 2024

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

VisRecall++: Analysing and Predicting Recallability of Information Visualisations from Gaze Behaviour (Dataset and Reproduction Data)

Apr 8, 2024

Wang, Yao; Bulling, Andreas, 2024, "VisRecall++: Analysing and Predicting Recallability of Information Visualisations from Gaze Behaviour (Dataset and Reproduction Data)", https://doi.org/10.18419/DARUS-3138, DaRUS, V1, UNF:6:NwphGtoYrBQqd2TyRh0OHA== [fileUNF]

This dataset contains stimuli and collected participant data of VisRecall++. The structure of the dataset is described in the README-File. Further, if you are interested in related codes of the publication, you can find a copy of the code repository (see Metadata for Research Software) within this dataset.

Dataset.py

Apr 8, 2024 - VisRecall++: Analysing and Predicting Recallability of Information Visualisations from Gaze Behaviour (Dataset and Reproduction Data)

Python Source Code - 5.7 KB -

main.py

Apr 8, 2024 - VisRecall++: Analysing and Predicting Recallability of Information Visualisations from Gaze Behaviour (Dataset and Reproduction Data)

Python Source Code - 4.3 KB -

Model.py

Apr 8, 2024 - VisRecall++: Analysing and Predicting Recallability of Information Visualisations from Gaze Behaviour (Dataset and Reproduction Data)

Python Source Code - 2.0 KB -

README.md

Apr 8, 2024 - VisRecall++: Analysing and Predicting Recallability of Information Visualisations from Gaze Behaviour (Dataset and Reproduction Data)

Markdown Text - 1.6 KB -