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

DOI

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.

You may find the most recent version of the source code on GitHub: https://github.com/Noeliel/GraphVQA-Explorer

Identifier
DOI https://doi.org/10.18419/DARUS-3589
Metadata Access https://darus.uni-stuttgart.de/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.18419/DARUS-3589
Provenance
Creator Schäfer, Noel; Tilli, Pascal; Munz-Körner, Tanja ORCID logo; Künzel, Sebastian ORCID logo; Vidyapu, Sandeep ORCID logo; Vu, Ngoc Thang ORCID logo; Weiskopf, Daniel ORCID logo
Publisher DaRUS
Contributor Tilli, Pascal; Munz-Körner, Tanja
Publication Year 2023
Funding Reference DFG EXC 2075 - 390740016
Rights MIT License; info:eu-repo/semantics/openAccess; https://spdx.org/licenses/MIT.html
OpenAccess true
Contact Tilli, Pascal (University of Stuttgart); Munz-Körner, Tanja (University of Stuttgart)
Representation
Resource Type Dataset
Format application/zip
Size 2813459
Version 1.0
Discipline Other