BIPED (Barcelona Images for Perceptual Edge Detection)

Introduced by Soria et al. in Dense Extreme Inception Network: Towards a Robust CNN Model for Edge Detection


It contains 250 outdoor images of 1280$\times$720 pixels each. These images have been carefully annotated by experts on the computer vision field, hence no redundancy has been considered. In spite of that, all results have been cross-checked several times in order to correct possible mistakes or wrong edges by just one subject. This dataset is publicly available as a benchmark for evaluating edge detection algorithms. The generation of this dataset is motivated by the lack of edge detection datasets, actually, there is just one dataset publicly available for the edge detection task published in 2016 (MDBD: Multicue Dataset for Boundary Detection—the subset for edge detection). The level of details of the edge level annotations in the BIPED’s images can be appreciated looking at the GT, see Figs above.

BIPED dataset has 250 images in high definition. Thoses images are already split up for training and testing. 200 for training and 50 for testing.


The current version is the second one.


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