Captioning Images with Diverse Objects
Table 8: DCC and NOC both using GloVe on MSCOCO dataset.
['Model', 'F1 (%)', 'METEOR (%)']
One aspect of difference between NOC and DCC is that NOC uses GloVe embeddings in it’s language model whereas DCC uses word2vec embeddings to select similar objects for transfer. In order to make a fair comparison of DCC with NOC, it is also important to consider the setting where both models use the same word-embedding. We modify the transfer approach in DCC and replace word2vec with GloVe embeddings. From Table. Thus, the embeddings themselves do not play as significant a role as the joint training approach.