Video Captioning with Boundary-aware Hierarchical Language Decoding and Joint Video Prediction
Table 1. Comparisons of the video captioning results of different methods on the MSVD dataset.
['Model', 'BLEU 4', 'METEOR', 'CIDEr']
Comparing among different baselines of our method, we can see that adding each additional component (including BD, SA, VP and HLM) further improves the performance, which demonstrates the effectiveness of each individual component. In our model, we share the soft attention module between the video features and the language features, while a common way is to use two different attention modules. It can be seen that the proposed shared attention module achieves better performance. Our final model with beam search, BI + BD + SA + VP + HLM, achieves the best performance in all the baselines across all metrics. Compare with the other approaches trained with the single training dataset, our final model achieves the state-of-the-art performance in BLEU 4 and CIDEr Score.