Search Results for author: Roman Suvorov

Found 8 papers, 5 papers with code

Resolution-robust Large Mask Inpainting with Fourier Convolutions

2 code implementations15 Sep 2021 Roman Suvorov, Elizaveta Logacheva, Anton Mashikhin, Anastasia Remizova, Arsenii Ashukha, Aleksei Silvestrov, Naejin Kong, Harshith Goka, Kiwoong Park, Victor Lempitsky

We find that one of the main reasons for that is the lack of an effective receptive field in both the inpainting network and the loss function.

Image Inpainting LAMA

Perceptual Gradient Networks

1 code implementation5 May 2021 Dmitry Nikulin, Roman Suvorov, Aleksei Ivakhnenko, Victor Lempitsky

The use of perceptual loss however incurs repeated forward-backward passes in a large image classification network as well as a considerable memory overhead required to store the activations of this network.

Fine-tuning Image Classification +1

DeepLandscape: Adversarial Modeling of Landscape Video

1 code implementation21 Aug 2020 Elizaveta Logacheva, Roman Suvorov, Oleg Khomenko, Anton Mashikhin, Victor Lempitsky

Furthermore, by fitting the learned models to a static landscape image, the latter can be reenacted in a realistic way.

SEIGAN: Towards Compositional Image Generation by Simultaneously Learning to Segment, Enhance, and Inpaint

no code implementations19 Nov 2018 Pavel Ostyakov, Roman Suvorov, Elizaveta Logacheva, Oleg Khomenko, Sergey I. Nikolenko

We present a novel approach to image manipulation and understanding by simultaneously learning to segment object masks, paste objects to another background image, and remove them from original images.

Image Generation Image Manipulation

Label Denoising with Large Ensembles of Heterogeneous Neural Networks

no code implementations12 Sep 2018 Pavel Ostyakov, Elizaveta Logacheva, Roman Suvorov, Vladimir Aliev, Gleb Sterkin, Oleg Khomenko, Sergey I. Nikolenko

Despite recent advances in computer vision based on various convolutional architectures, video understanding remains an important challenge.

Data Augmentation Denoising +4

The Limitations of Cross-language Word Embeddings Evaluation

1 code implementation SEMEVAL 2018 Amir Bakarov, Roman Suvorov, Ilya Sochenkov

The aim of this work is to explore the possible limitations of existing methods of cross-language word embeddings evaluation, addressing the lack of correlation between intrinsic and extrinsic cross-language evaluation methods.

Word Embeddings

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