217 citations · 235 across the 7 of their papers we have counts for
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stat.ML2017★ 217 cited
Strengths and Weaknesses of Deep Learning Models for Face Recognition Against Image Degradations
Klemen Grm, Vitomir Štruc, Anais Artiges +2
Deep convolutional neural networks (CNNs) based approaches are the state-of-the-art in various computer vision tasks, including face recognition. Considerable research effort is cu…
cs.CV2017★ 12 cited
UG^2: a Video Benchmark for Assessing the Impact of Image Restoration and Enhancement on Automatic Visual Recognition
Rosaura G. Vidal, Sreya Banerjee, Klemen Grm +2
Advances in image restoration and enhancement techniques have led to discussion about how such algorithmscan be applied as a pre-processing step to improve automatic visual recogni…