Corpus ID: 218596308

RetinotopicNet: An Iterative Attention Mechanism Using Local Descriptors with Global Context

@article{Kurbiel2020RetinotopicNetAI,
  title={RetinotopicNet: An Iterative Attention Mechanism Using Local Descriptors with Global Context},
  author={Thomas Kurbiel and Shahrzad Khaleghian},
  journal={ArXiv},
  year={2020},
  volume={abs/2005.05701}
}
Convolutional Neural Networks (CNNs) were the driving force behind many advancements in Computer Vision research in recent years. This progress has spawned many practical applications and we see an increased need to efficiently move CNNs to embedded systems today. However traditional CNNs lack the property of scale and rotation invariance: two of the most frequently encountered transformations in natural images. As a consequence CNNs have to learn different features for same objects at… Expand
1 Citations
Study of Convolutional Neural Networks for Global Parametric Motion Estimation on Log-Polar Imagery
TLDR
Experiments on existing image datasets using synthetic image deformations reveal that standard CNNs can successfully learn to estimate global parametric motion on log-polar images with accuracies comparable to or better than with Cartesian images. Expand

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