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Wildest Faces: Face Detection and Recognition in Violent Settings (arxiv.org)
3 points by blopeur on Jun 2, 2018 | hide | past | pdf | discuss on HN

In plain words: A new collection of celebrity faces pulled from violent movie scenes, where faces are blurry, tiny, turned away or partly hidden, gives a harder test for face-finding and identification systems. The best current systems struggle on these scenes, unlike on cleaner photos.

Abstract

With the introduction of large-scale datasets and deep learning models capable of learning complex representations, impressive advances have emerged in face detection and recognition tasks. Despite such advances, existing datasets do not capture the difficulty of face recognition in the wildest scenarios, such as hostile disputes or fights. Furthermore, existing datasets do not represent completely unconstrained cases of low resolution, high blur and large pose/occlusion variances. To this end, we introduce the Wildest Faces dataset, which focuses on such adverse effects through violent scenes. The dataset consists of an extensive set of violent scenes of celebrities from movies. Our experimental results demonstrate that state-of-the-art techniques are not well-suited for violent scenes, and therefore, Wildest Faces is likely to stir further interest in face detection and recognition research.

Mehmet Kerim Yucel, Yunus Can Bilge, Oguzhan Oguz, Nazli Ikizler-Cinbis, Pinar Duygulu, Ramazan Gokberk Cinbis
arXiv:1805.07566 · cs.CV · submitted May 19, 2018
abstract · pdf · html · Submitted to BMVC 2018

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