Empirical Autopsy of Deep Video Captioning Frameworks
Table 1: Results of depth variation in GRU-based language model.
['Model Depth', 'B-4', 'M', 'C', 'R']
In our experiments, Gated Recurrent Units (GRUs) based language models are used. In our analysis, we vary the number of layers in the language model to observe the performance change. Our empirical evaluation shows that two-layers language model performs best under our settings (type and size of dataset, encoder-decoder framework), as compared to a one or a three layer model. Increasing layers from one to two generally improves the captioning performance. However, increasing the layers further to three does not result in performance gain. In fact, it slightly deteriorates the scores across all metrics.