Self-supervised learning using motion and visualizing convolutional neural networks
<p>We propose a novel method for learning convolutional image representations without manual supervision. We use motion in the form of optical-flow, to supervise representations of static images. Training a network to predict flow from a single image can be needlessly difficult due to intrinsi...
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| Format: | Thesis |
| Language: | English |
| Published: |
2018
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