Contents
Table 6.2: Comparison between two different training methodologies: I2T and T2I. BoW means unsing unigram word features and 2g means using bigram. All results are given in Recall@10: avg_txt. nhu is the hidden layer in the textual model, while nemb is the size of embedding dimension.
['[BOLD] Training methodology: I2T vs T2I Models', '[BOLD] Training methodology: I2T vs T2I image annotation', '[BOLD] Training methodology: I2T vs T2I image annotation', '[BOLD] Training methodology: I2T vs T2I image search', '[BOLD] Training methodology: I2T vs T2I image search']
I2T and T2I. We notice that this choice actually does impact the performance of our system in a peculiar way; it specializes it to a particular task. We compare the performance across several models architectures and consistently notice the same phenomenon. Hence for all future results, whenever we refer to image annotation we report I2T results, and for image search we report T2I results.