1 to 10 of 31 Results
Jul 25, 2023
Schäfer, Noel; Tilli, Pascal; Munz-Körner, Tanja; Künzel, Sebastian; Vidyapu, Sandeep; Vu, Ngoc Thang; Weiskopf, Daniel, 2023, "Model Parameters and Evaluation Data for our Visual Analysis System for Scene-Graph-Based Visual Question Answering", https://doi.org/10.18419/darus-3597, DaRUS, V1
Pretrained model parameters and pregenerated evaluation data for our visual analysis system for scene-graph-based visual question answering (https://doi.org/10.18419/darus-3589). |
Jul 25, 2023 -
Model Parameters and Evaluation Data for our Visual Analysis System for Scene-Graph-Based Visual Question Answering
7Z Archive - 156.9 MB -
MD5: 1900cd3a2a3a6836888073127a4978f5
Pregenerated evaluation data |
Jul 25, 2023 -
Model Parameters and Evaluation Data for our Visual Analysis System for Scene-Graph-Based Visual Question Answering
7Z Archive - 2.5 GB -
MD5: 6521038f236d50fd2d24aad27ca30bb4
Pretrained model parameters |
Jul 25, 2023
Munz-Körner, Tanja; Künzel, Sebastian; Weiskopf, Daniel, 2023, "Supplemental Material for "Visual-Explainable AI: The Use Case of Language Models"", https://doi.org/10.18419/darus-3456, DaRUS, V1
Supplemental material for the poster "Visual-Explainable AI: The Use Case of Language Models" published at the International Conference on Data-Integrated Simulation Science 2023. Collection of videos and images showing our interactive visualization systems for exploring language... |
MPEG-4 Video - 103.2 MB -
MD5: 528bdd106b37c293308d8fc175ae0dd7
Video demonstrating our classification system. |
ZIP Archive - 16.8 MB -
MD5: 01987c2f7fe58478c03b52bdc3527c66
Screenshots of our classification system. |
MPEG-4 Video - 94.4 MB -
MD5: 870a6bea2d5039fcdf5f88694e277244
Video demonstrating our neural machine translation system. |
ZIP Archive - 2.1 MB -
MD5: 45e317e218545d8d33aaa99f0bb3ffef
Screenshots of our neural machine translation system. |
Jul 25, 2023
Schäfer, Noel; Tilli, Pascal; Munz-Körner, Tanja; Künzel, Sebastian; Vidyapu, Sandeep; Vu, Ngoc Thang; Weiskopf, Daniel, 2023, "Visual Analysis System for Scene-Graph-Based Visual Question Answering", https://doi.org/10.18419/darus-3589, DaRUS, V1
Source code of our visual analysis system to explore scene-graph-based visual question answering. This approach is built on top of the state-of-the-art GraphVQA framework which was trained on the GQA dataset. Instructions on how to use our system can be found in the README. |
ZIP Archive - 2.7 MB -
MD5: b8a072d4e77d1306ec3e027a5537c2cc
Source code of our visual analytics system |