• Corpus ID: 25985931

Saliency Benchmarking: Separating Models, Maps and Metrics

@article{Kmmerer2017SaliencyBS,
  title={Saliency Benchmarking: Separating Models, Maps and Metrics},
  author={Matthias K{\"u}mmerer and Thomas S. A. Wallis and Matthias Bethge},
  journal={ArXiv},
  year={2017},
  volume={abs/1704.08615}
}
The field of fixation prediction is heavily model-driven, with dozens of new models published every year. [] Key Method We define a saliency model to be a probabilistic model of fixation density prediction and, inspired by Bayesian decision theory, a saliency map to be a metric-specific prediction derived from the model density which maximizes the expected performance on that metric.

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