5 citations · 5 across the 3 of their papers we have counts for
4 papers
AIM 2024 Challenge on Video Super-Resolution Quality Assessment: Methods and Results
Ivan Molodetskikh, Artem Borisov, Dmitriy Vatolin +24
This paper presents the Video Super-Resolution (SR) Quality Assessment (QA) Challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with E…
Combining Contrastive and Supervised Learning for Video Super-Resolution Detection
Viacheslav Meshchaninov, Ivan Molodetskikh, Dmitriy Vatolin
Upscaled video detection is a helpful tool in multimedia forensics, but it is a challenging task that involves various upscaling and compression algorithms. There are many resoluti…
Temporally Coherent Person Matting Trained on Fake-Motion Dataset
Ivan Molodetskikh, Mikhail Erofeev, Andrey Moskalenko +1
We propose a novel neural-network-based method to perform matting of videos depicting people that does not require additional user input such as trimaps. Our architecture achieves…
Perceptually Motivated Method for Image Inpainting Comparison
Ivan Molodetskikh, Mikhail Erofeev, Dmitry Vatolin
The field of automatic image inpainting has progressed rapidly in recent years, but no one has yet proposed a standard method of evaluating algorithms. This absence is due to the p…