Commit
•
54500ea
1
Parent(s):
71ae00f
Update README.md
Browse files
README.md
CHANGED
|
@@ -6,6 +6,9 @@ This model can be used to assign an object-to-caption semantic ness score, which
|
|
| 6 |
|
| 7 |
To take advantage of the overlapping between the visual context and the caption, and to extract global information from each visual (i.e., object, scene, etc) we use BERT as an embedding layer followed by a shallow CNN (tri-gram kernel) (Kim, 2014).
|
| 8 |
|
|
|
|
|
|
|
|
|
|
| 9 |
|
| 10 |
For datasets that are less than 100K please have look at our [shallow model](https://github.com/ahmedssabir/Semantic-Relatedness-Based-Reranker-for-Text-Spotting)
|
| 11 |
|
|
|
|
| 6 |
|
| 7 |
To take advantage of the overlapping between the visual context and the caption, and to extract global information from each visual (i.e., object, scene, etc) we use BERT as an embedding layer followed by a shallow CNN (tri-gram kernel) (Kim, 2014).
|
| 8 |
|
| 9 |
+
Please refer to [Github](https://github.com/ahmedssabir/Visual-Semantic-Relatedness-Dataset-for-Image-Captioning) for more information.
|
| 10 |
+
|
| 11 |
+
|
| 12 |
|
| 13 |
For datasets that are less than 100K please have look at our [shallow model](https://github.com/ahmedssabir/Semantic-Relatedness-Based-Reranker-for-Text-Spotting)
|
| 14 |
|