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The goal of this work is to recognise phrases and sentences being spoken by a talking face, with or without the audio. Unlike previous works that have focussed on recognising a limited number of words or phrases, we tackle lip reading as an open-world problem – unconstrained natural language sentences, and in the wild videos. Our key contributions are: (1) a Watch, Listen, Attend and Spell...
Automatically describing the content of an image is a fundamental problem in artificial intelligence that connects computer vision and natural language processing. In this paper, we present a generative model based on a deep recurrent architecture that combines recent advances in computer vision and machine translation and that can be used to generate natural sentences describing an image. The model...
Recent studies have shown that K-means, with larger K, can effectively learn local image patch features; accompanied with appropriate pooling strategies, it performs very well in many visual object recognition tasks. An improved K-means cluster algorithm, GEV-Kmeans, based on the Generalized Extreme Value (GEV) distribution, is proposed in this paper. Our key observation is that the squared distance...
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