Unsupervised learning of depth and motion

@article{Konda2013UnsupervisedLO,
  title={Unsupervised learning of depth and motion},
  author={Kishore Reddy Konda and Roland Memisevic},
  journal={CoRR},
  year={2013},
  volume={abs/1312.3429}
}
We present a model for the joint estimation of disparity and motion. The model is based on learning about the interrelations between images from multiple cameras, multiple frames in a video, or the combination of both. We show that learning depth and motion cues, as well as their combinations, from data is possible within a single type of architecture and a single type of learning algorithm, by using biologically inspired “complex cell” like units, which encode correlations between the pixels… CONTINUE READING
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