Name
Abstract | ||
|---|---|---|
ABSTRACTIn 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. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1145/3474085.3477940 | International Multimedia Conference |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fan Yu | 1 | 0 | 2.03 |
| Haonan Wang | 2 | 0 | 1.35 |
| Tongwei Ren | 3 | 328 | 30.22 |
| Jinhui Tang | 4 | 5180 | 212.18 |
| Gang-Shan Wu | 5 | 27 | 6.75 |
| Jingjing Chen | 6 | 125 | 22.05 |
| Zhenzhong Kuang | 7 | 62 | 11.86 |