Generating Video Descriptions with Topic Guidance
Table 2. Captioning performance of the predefined categories and data-driven topics using the best caption model with topic guidance. The acronyms B, M, R, C denote BLEU@4, METEOR, ROUGE-L and CIDEr respectively.
['[EMPTY]', 'B', 'M', 'R', 'C']
We can see that the different topic guidances (the second to forth rows) all greatly improve the performance of the multimodal baseline (the first row). The guidance from predicted data-driven topics outperforms that from the predicted category tags on all four evaluation metrics, and the Student’s t-test shows the improvement is significant with p-value<0.002. Even compared with the category tags assigned by video uploaders, the predicted data-driven topics also slightly boost the captioning performance on multiple metrics with the Student’s t-test p-value<0.01 on BLEU@4 and CIDEr metrics, which shows the performance gain is robust. These results suggest that the data-driven topics are more suitable as the topic representation than predefined topics for video captioning.