Ivan Andreevich MOLODETSKIKH
Lomonosov Moscow State University, Ivannikov Institute for System Programming of the Russian Academy of Sciences
Russian Federation

Received his master degree in computer science from the Moscow State University in 2020. He is currently a postgraduate student at the MSU Graphics & Media Lab. His research interests include super-resolution, semantic video matting and machine learning. Ivan supervised the development of MSU video upscalers and SR+codec benchmarks and was one of the organizers of the ECCV-AIM 2024 video super-resolution quality assessment challenge.

Mikhail Viktorovich EROFEEV
Lomonosov Moscow State University
Russian Federation

Cand. Sci. (Phys.-Math.). He graduated from the Computer Science department of Lomonosov Moscow State University, and currently he is a researcher at the MSU Graphics & Media Lab. His research interests include video and image matting, and machine learning. Mikhail is one of the major contributors to the video matting methods benchmark.

Andrey Viktorovich MOSKALENKO
Lomonosov Moscow State University
Russian Federation

Received his master degree in computer science from the Moscow State University in 2023. He is currently a postgraduate student at the MSU Graphics & Media Lab. His research interests involve visual attention modeling, interactive segmentation, image inpainting and video quality assessment. Andrey is one of the core contributors to the subjective media quality assessment platform.

Dmitriy Sergeevich VATOLIN
Lomonosov Moscow State University, Ivannikov Institute for System Programming of the Russian Academy of Sciences
Russian Federation

Cand. Sci. (Phys.-Math.) from Moscow State University, head of the MSU Graphics & Media Lab and MSU AI Institute Video Analysis Lab, and a researcher at the Research Centre for Trusted AI of ISP RAS. His research interests include compression methods, video processing, 3D video techniques (depth from motion, focus and other cues, video matting, background restoration, high-quality stereo generation), as well as video quality assessment and robustness of modern video quality metrics. He is a key cofounder of the 3D video quality measurement project, his most known project is the annual MSU Video Codecs Comparison, that includes up to 25 modern codecs compared subjectively and objectively in several nominations with detailed 20000+ charts.