Integrating Image Captioning with Rule-based Entity Masking
Table 3: Diversity: Comparison of vocab size (VS) and novel captions. Base-IC and Interpret-IC use +Obj → VisualEntity features.
['[EMPTY]', 'Base-bs', 'Adv-bs', 'Base-IC', 'Interpret-IC']
Although our aim is not to achieve diverse captions, to comprehend whether our proposed Base-IC and Interpret-IC models generate best (i.e., Top-1) diverse and interesting caption. We compared our models with other diverse caption generation baselines that compare best generated caption using diversity measures described earlier. We observe that, our Interpret-IC model cannot exceed scores of the baseline trained to generate diverse captions in an adversarial setting (i.e., Adv-bs). However, with less effort and simple masking we could see a significant jump on the standard caption model (i.e., Base-bs).