Video Captioning with Guidance of Multimodal Latent Topics
Table 3. Caption performance of M&M TGM and state-of-the-art methods on MSR-VTT and Youtube2Text datasets.
['dataset', 'model', 'BLEU4', 'METEOR', 'CIDEr']
Our method achieves significant better performance than prior works on MSR-VTT dataset, for example, the BLEU@4 achieves 7.08% relative improvement than the previous best performance. For Youtube2Text dataset, the METEOR and CIDERr scores improved significantly but our performance on BLEU@4 is lower than the SCN-LSTM. The BLEU@4 metric focuses on the syntactic agreement, while METEOR and CIDEr concern more about semantic meanings. Therefore, we consider the sentence generated from M&M TGM are more semantically relevant with the video content.