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Reproducibility Companion Paper

Authors :
Zhenzhong Kuang
Fan Yu
Jinhui Tang
Gangshan Wu
Tongwei Ren
Jingjing Chen
Haonan Wang
Source :
ACM Multimedia
Publication Year :
2021
Publisher :
ACM, 2021.

Abstract

In this companion paper, we provide the details of the reproducibility artifacts of the paper "Visual Relation of Interest Detection" presented at MM'20. Visual Relation of Interest Detection (VROID) aims to detect visual relations that are important for conveying the main content of an image. In this paper, we explain the file structure of the source code and publish the details of our ViROI dataset, which can be used to retrain the model with custom parameters. We also detail the scripts for component analysis and comparison with other methods and list the parameters that can be modified for custom training and inference.

Details

Database :
OpenAIRE
Journal :
Proceedings of the 29th ACM International Conference on Multimedia
Accession number :
edsair.doi...........1f102e098031078a535fa76182915e74