Mooney, Ray
<p>Apr 01, 2016 01:13 PM</p>
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see Ray's talk today... below:
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<p>Title: Generating Natural-Language Video Descriptions using LSTM Recurrent Neural Networks<br />
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We present a method for<b> automatically generating English sentences describing short videos</b> using<b> deep neural networks</b></p>
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<b>.</b> Specifically, we apply <b>convolutional and Long Short-Term Memory (LSTM) recurrent networks</b> to translate <b>videos to English descriptions using an encoder/decoder framework</b>. </p>
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<b>A sequence of image frames (represented using deep visual features) is first mapped to a vector encoding</b> the full video, and then<b> this encoding is mapped to a sequence of words</b></p>
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. We have also explored how statistical linguistic knowledge mined from large text corpora, specifically LSTM language models and lexical embeddings, can improve the descriptions. Experimental evaluation on a corpus of short YouTube videos and movie clips annotated b<b>y Descriptive Video Service</b> demonstrate the capabilities of the technique by comparing its output to human-generated descriptions.<br />
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Raymond J. Mooney is a Professor in the Department of Computer Science at the <b>University of Texas at Austin</b>. He received his<b> Ph.D. in 1988</b> from the University of Illinois at Urbana/Champaign. He is an author of over 160 published research papers, primarily in the areas of machine learning and natural language processing. He was the President of the International Machine Learning Society from 2008-2011, program co-chair for AAAI 2006, general chair for HLT-EMNLP 2005, and co-chair for ICML 1990. He is a Fellow of the American Association for Artificial Intelligence, the Association for Computing Machinery, and the Association for Computational Linguistics and the recipient of best paper awards from AAAI-96, KDD-04, ICML-05 and ACL-07.
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