9 citations · 14 across the 6 of their papers we have counts for
6 papers
NTIRE 2026 Challenge on Video Saliency Prediction: Methods and Results
Andrey Moskalenko, Alexey Bryncev, Ivan Kosmynin +40
This paper presents an overview of the NTIRE 2026 Challenge on Video Saliency Prediction. The goal of the challenge participants was to develop automatic saliency map prediction me…
NTIRE 2026 Challenge on Robust AI-Generated Image Detection in the Wild
Aleksandr Gushchin, Khaled Abud, Ekaterina Shumitskaya +51
This paper presents an overview of the NTIRE 2026 Challenge on Robust AI-Generated Image Detection in the Wild, held in conjunction with the NTIRE workshop at CVPR 2026. The goal o…
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…
Deep Two-Stage High-Resolution Image Inpainting
Andrey Moskalenko, Mikhail Erofeev, Dmitriy Vatolin
In recent years, the field of image inpainting has developed rapidly, learning based approaches show impressive results in the task of filling missing parts in an image. But most d…
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…
Improving Video Compression With Deep Visual-Attention Models
Vitaliy Lyudvichenko, Mikhail Erofeev, Alexander Ploshkin +1
Recent advances in deep learning have markedly improved the quality of visual-attention modelling. In this work we apply these advances to video compression. We propose a compressi…