Abstract
We investigate if a deep Convolutional Neural Network can learn representations of local image patches that are usable in the important task of keypoint matching. We examine several possible loss functions for this correspondance task and show emprically that a newly suggested loss formulation allows a Convolutional Neural Network to find compact local image descriptors that perform comparably to state-of-the-art approaches.
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Osendorfer, C., Bayer, J., Urban, S., van der Smagt, P. (2013). Convolutional Neural Networks Learn Compact Local Image Descriptors. In: Lee, M., Hirose, A., Hou, ZG., Kil, R.M. (eds) Neural Information Processing. ICONIP 2013. Lecture Notes in Computer Science, vol 8228. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42051-1_77
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DOI: https://doi.org/10.1007/978-3-642-42051-1_77
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