One of the most important tasks on the edge between natural language processing (NLP) and computer vision (CV) is image captioning. There are many papers dedicated to researches in a field of improving image captioning models quality. However, compression of such models in order to be used on mobile devices is quite underexplored. More than that, such an important technique as knowledge distillation which is widely used for model compression isn’t mentioned in almost any of them. To fill this gap we applied the most efficient knowledge distillation approaches to several state-of-the-art image captioning architectures.
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