• Computer Science, Mathematics
  • Published in ArXiv 2017

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. However, progress in the field can be difficult to judge because models are compared using a variety of inconsistent metrics. As soon as a saliency map is optimized for a certain metric, it is penalized by other metrics. Here we propose a principled approach to solve the benchmarking problem: we separate the notions of saliency models and saliency maps. We define a saliency model to be a… CONTINUE READING
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