no code implementations • 29 Sep 2021 • Dmitry Senushkin, Iaroslav Melekhov, Mikhail Romanov, Anton Konushin, Juho Kannala, Arno Solin
We present a novel gradient-based multi-task learning (MTL) approach that balances training in multi-task systems by aligning the independent components of the training objective.
1 code implementation • 25 Sep 2020 • Mikhail Romanov, Nikolay Patatkin, Anna Vorontsova, Sergey Nikolenko, Anton Konushin, Dmitry Senyushkin
Our work shows that a model trained on this data along with conventional datasets can gain accuracy while predicting correct scene geometry.
1 code implementation • 18 Jun 2020 • Danil Galeev, Konstantin Sofiiuk, Danila Rukhovich, Mikhail Romanov, Olga Barinova, Anton Konushin
Based on this finding, we propose LayerMatch scheme for approximating the representation of a GAN generator that can be used for unsupervised domain-specific pretraining.
1 code implementation • 18 May 2020 • Dmitry Senushkin, Mikhail Romanov, Ilia Belikov, Anton Konushin, Nikolay Patakin
Our second contribution is a novel training strategy that allows us to train on a semi-dense sensor data when the ground truth depth map is not available.
Ranked #1 on
Depth Completion
on Matterport3D
no code implementations • 20 Nov 2018 • Nikita Durasov, Mikhail Romanov, Valeriya Bubnova, Pavel Bogomolov, Anton Konushin
Monocular depth estimation is the task of obtaining a measure of distance for each pixel using a single image.
Indoor Monocular Depth Estimation
Monocular Depth Estimation