322 citations · 1.4k across the 18 of their papers we have counts for
3 papers · 1 filter
DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks
Orest Kupyn, Volodymyr Budzan, Mykola Mykhailych +2
We present DeblurGAN, an end-to-end learned method for motion deblurring. The learning is based on a conditional GAN and the content loss . DeblurGAN achieves state-of-the art perf…
Repeatability Is Not Enough: Learning Affine Regions via Discriminability
Dmytro Mishkin, Filip Radenovic, Jiri Matas
A method for learning local affine-covariant regions is presented. We show that maximizing geometric repeatability does not lead to local regions, a.k.a features,that are reliably…
Working hard to know your neighbor's margins: Local descriptor learning loss
Anastasiya Mishchuk, Dmytro Mishkin, Filip Radenovic +1
We introduce a novel loss for learning local feature descriptors which is inspired by the Lowe's matching criterion for SIFT. We show that the proposed loss that maximizes the dist…