Authors
Christian Szegedy, Scott Reed, Dumitru Erhan, Dragomir Anguelov
Publication date
2014/12/3
Journal
arXiv preprint arXiv:1412.1441
Description
Abstract: Most high quality object detection approaches use the same scheme: salience-
based object proposal methods followed by post-classification using deep convolutional
features. In this work, we demonstrate that fully learnt, data-driven proposal generation
methods can effectively match the accuracy of their hand engineered counterparts, while
allowing for very efficient runtime-quality trade-offs. This is achieved by making several key
improvements to the MultiBox method [4], among which are an improved neural network ...
based object proposal methods followed by post-classification using deep convolutional
features. In this work, we demonstrate that fully learnt, data-driven proposal generation
methods can effectively match the accuracy of their hand engineered counterparts, while
allowing for very efficient runtime-quality trade-offs. This is achieved by making several key
improvements to the MultiBox method [4], among which are an improved neural network ...
Total citations
Scholar articles
C Szegedy, S Reed, D Erhan, D Anguelov - arXiv preprint arXiv:1412.1441, 2014
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