4 papers
ActGAN: Flexible and Efficient One-shot Face Reenactment
Ivan Kosarevych, Marian Petruk, Markian Kostiv +3
This paper introduces ActGAN - a novel end-to-end generative adversarial network (GAN) for one-shot face reenactment. Given two images, the goal is to transfer the facial expressio…
Fast and Efficient Model for Real-Time Tiger Detection In The Wild
Orest Kupyn, Dmitry Pranchuk
The highest accuracy object detectors to date are based either on a two-stage approach such as Fast R-CNN or one-stage detectors such as Retina-Net or SSD with deep and complex bac…
DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better
Orest Kupyn, Tetiana Martyniuk, Junru Wu +1
We present a new end-to-end generative adversarial network (GAN) for single image motion deblurring, named DeblurGAN-v2, which considerably boosts state-of-the-art deblurring effic…
Safe Augmentation: Learning Task-Specific Transformations from Data
Irynei Baran, Orest Kupyn, Arseny Kravchenko
Data augmentation is widely used as a part of the training process applied to deep learning models, especially in the computer vision domain. Currently, common data augmentation te…