Integrate Image Representation to Text Model on Sentence Level: a Semi-supervised Framework
Table 3: Result of SemEval 2018 Task 11 (MCScript) on different train/test image bases.
['[BOLD] Train Base', '[BOLD] Test Base', '[BOLD] Test']
In order to study the effect of image memory base size on experimental results, we alternate image base in train and test process. As shown in Table. When we shrink the test image memory base to the Flicker30k, the integrated model performance reduces, but is still higher than using 30k image both in train and test. More importantly, when the model is trained on the Flicker30k image base, using a bigger one does not contribute to test performance. These results suggest that the framework could work better as the size of the image base in train and test increases.