Deconvolution of Image Sequences with a Learning FFT-based Approach. - Iaroslav Koshelev; Andrey Somov; Stamatios Lefkimmiatis; Antonio Jose Rodríguez-Sánchez (ISIE, 2020)

Learned Gradient Descent Performance in Bicubic Super-Resolution Task. - Iaroslav Koshelev; Andrey Somov (IECON, 2021)

NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results. - Ren Yang; Radu Timofte; Jing Liu 031; Yi Xu 003; Xinjian Zhang; Minyi Zhao; Shuigeng Zhou; Kelvin C. K. Chan; Shangchen Zhou; Xiangyu Xu 002; Chen Change Loy; Xin Li 106; et al. (CoRR, 2021)

DeepRLS: A Recurrent Network Architecture with Least Squares Implicit Layers for Non-blind Image Deconvolution. - Iaroslav Koshelev; Daniil Selikhanovych; Stamatios Lefkimmiatis (CoRR, 2021)

Learning Sparse and Low-Rank Priors for Image Recovery via Iterative Reweighted Least Squares Minimization. - Stamatios Lefkimmiatis; Iaroslav Koshelev (ICLR, 2023)

Iterative Reweighted Least Squares Networks With Convergence Guarantees for Solving Inverse Imaging Problems. - Iaroslav Koshelev; Stamatios Lefkimmiatis (CoRR, 2023)

Drone-Aided Detection of Weeds: Transfer Learning for Embedded Image Processing. - Iaroslav Koshelev; Maxim Savinov; Alexander Menshchikov; Andrey Somov (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023)

Robust Two-View Geometry Estimation with Implicit Differentiation. - Vladislav A. Pyatov; Iaroslav Koshelev; Stamatios Lefkimmiatis (IROS, 2024)

A Modular Conditional Diffusion Framework for Image Reconstruction. - Magauiya Zhussip; Iaroslav Koshelev; Stamatios Lefkimmiatis (NeurIPS, 2024)

One-Step Residual Shifting Diffusion for Image Super-Resolution via Distillation. - Daniil Selikhanovych; David Li 004; Aleksei Leonov; Nikita Gushchin; Sergei Kushneriuk; Alexander Filippov; Evgeny Burnaev; Iaroslav Koshelev; Alexander Korotin (CoRR, 2025)