How does the inference efficiency of VGG-style very deep convolutional networks compare to shallow baselines w

Abstract

Abstract: Interest in Artificial Intelligence (AI) and its applications has seen unprecedented growth in the last few years. This success can be partly attributed to the advancements made in the sub-fields of AI such as machine learning, computer vision, and natural language processing. Much of the growth in these fields has been made possible with deep learning, a sub-area of machine learning that uses artificial neural networks. This has created significant interest in the integration of vision and language. In this survey, we focus on ten prominent tasks that integrate language and vision by discussi

Research Question

How does the inference efficiency of VGG-style very deep convolutional networks compare to shallow baselines when processing high-resolution video frames with corresponding subtitles?

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