Original paper
Learning Spatio-Temporal Representation with Pseudo-3D Residual Networks
Published: Oct 1, 2017
Abstract
Convolutional Neural Networks (CNN) have been regarded as a powerful class of models for image recognition problems. Nevertheless, it is not trivial when utilizing a CNN for learning spatio-temporal video representation. A few studies have shown that performing 3D convolutions is a rewarding approach to capture both spatial and temporal dimensions in videos. However, the development of a very deep 3D CNN from scratch results in expensive...
Paper Details
Title
Learning Spatio-Temporal Representation with Pseudo-3D Residual Networks
Published Date
Oct 1, 2017
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