Extended Visual Analysis System for Scene-Graph-Based Visual Question Answering

DOI

Source code of our extended 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.

Additionally, it is an improved version of our system that can be found here

Instructions on how to use our system can be found in the README.

You may find more information on GitHub: https://github.com/Noeliel/GraphVQA-Explorer

Identifier
DOI https://doi.org/10.18419/DARUS-3909
Related Identifier IsCitedBy https://doi.org/10.1186/s42492-025-00185-y
Metadata Access https://darus.uni-stuttgart.de/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.18419/DARUS-3909
Provenance
Creator Schäfer, Noel ORCID logo; Künzel, Sebastian ORCID logo; Tilli, Pascal ORCID logo; Munz-Körner, Tanja ORCID logo; Vidyapu, Sandeep ORCID logo; Vu, Ngoc Thang ORCID logo; Weiskopf, Daniel ORCID logo
Publisher DaRUS
Contributor Künzel, Sebastian; Tilli, Pascal; Munz-Körner, Tanja
Publication Year 2025
Funding Reference DFG EXC 2075 - 390740016
Rights MIT License; info:eu-repo/semantics/openAccess; https://spdx.org/licenses/MIT.html
OpenAccess true
Contact Künzel, Sebastian (University of Stuttgart); Tilli, Pascal (University of Stuttgart); Munz-Körner, Tanja (University of Stuttgart)
Representation
Resource Type Dataset
Format application/octet-stream
Size 2813510
Version 1.0
Discipline Computer Science; Computer Science, Electrical and System Engineering; Engineering Sciences