Video Captioning with Guidance of Multimodal Latent Topics
Table 4. Comparison of generalization ability of the vanilla model and our proposed M&M TGM model. The models are trained on MSR-VTT training set and evaluated on the Youtube2Text testing set.
['[EMPTY]', 'BLEU4', 'METEOR', 'ROUGE [ITALIC] l', 'CIDEr']
Generalization Ability: To evaluate the generalization ability of our proposed method, we conduct the cross dataset experiment. We train M&M TGM on MSR-VTT dataset and test its performance on the Youtube2Text dataset. We can see that the proposed M&M TGM works significantly better than Vanilla model for cross datasets evaluation on all four metrics, which demonstrates that our method not only can improve the caption performance for in-domain videos but also generalize well on videos in the wild.