Zobrazeno 1 - 10
of 106
pro vyhledávání: '"Orlov, Nikita"'
Autor:
Peruzzo, Elia, Menapace, Willi, Goel, Vidit, Arrigoni, Federica, Tang, Hao, Xu, Xingqian, Chopikyan, Arman, Orlov, Nikita, Hu, Yuxiao, Shi, Humphrey, Sebe, Nicu, Ricci, Elisa
In the last few years, Neural Painting (NP) techniques became capable of producing extremely realistic artworks. This paper advances the state of the art in this emerging research domain by proposing the first approach for Interactive NP. Considering
Externí odkaz:
http://arxiv.org/abs/2307.16441
Universal Image Segmentation is not a new concept. Past attempts to unify image segmentation in the last decades include scene parsing, panoptic segmentation, and, more recently, new panoptic architectures. However, such panoptic architectures do not
Externí odkaz:
http://arxiv.org/abs/2211.06220
Autor:
Wang, Yulin, Yue, Yang, Xu, Xinhong, Hassani, Ali, Kulikov, Victor, Orlov, Nikita, Song, Shiji, Shi, Humphrey, Huang, Gao
Recent research has revealed that reducing the temporal and spatial redundancy are both effective approaches towards efficient video recognition, e.g., allocating the majority of computation to a task-relevant subset of frames or the most valuable im
Externí odkaz:
http://arxiv.org/abs/2209.13465
Autor:
Ma, Xu, Zhou, Yuqian, Xu, Xingqian, Sun, Bin, Filev, Valerii, Orlov, Nikita, Fu, Yun, Shi, Humphrey
Image rasterization is a mature technique in computer graphics, while image vectorization, the reverse path of rasterization, remains a major challenge. Recent advanced deep learning-based models achieve vectorization and semantic interpolation of ve
Externí odkaz:
http://arxiv.org/abs/2206.04655
Autor:
Wang, Yulin, Yue, Yang, Lin, Yuanze, Jiang, Haojun, Lai, Zihang, Kulikov, Victor, Orlov, Nikita, Shi, Humphrey, Huang, Gao
Recent works have shown that the computational efficiency of video recognition can be significantly improved by reducing the spatial redundancy. As a representative work, the adaptive focus method (AdaFocus) has achieved a favorable trade-off between
Externí odkaz:
http://arxiv.org/abs/2112.14238
Autor:
Jain, Jitesh, Singh, Anukriti, Orlov, Nikita, Huang, Zilong, Li, Jiachen, Walton, Steven, Shi, Humphrey
Finetuning a pretrained backbone in the encoder part of an image transformer network has been the traditional approach for the semantic segmentation task. However, such an approach leaves out the semantic context that an image provides during the enc
Externí odkaz:
http://arxiv.org/abs/2112.12782
Autor:
Rodin, Dmitry, Orlov, Nikita
Glare is a phenomenon that occurs when the scene has a reflection of a light source or has one in it. This luminescence can hide useful information from the image, making text recognition virtually impossible. In this paper, we propose an approach to
Externí odkaz:
http://arxiv.org/abs/1911.05189
Text detection in natural images is a challenging but necessary task for many applications. Existing approaches utilize large deep convolutional neural networks making it difficult to use them in real-world tasks. We propose a small yet relatively pr
Externí odkaz:
http://arxiv.org/abs/1908.08994
Publikováno v:
In International Journal of Hydrogen Energy 22 April 2022 47(34):15198-15208
Autor:
Orlov, Nikita A.1,2 (AUTHOR) n.orlov858@yandex.ru, Kryukova, Elena V.1 (AUTHOR) evkr@mail.ru, Efremenko, Anastasia V.1 (AUTHOR) aefr@mail.ru, Yakimov, Sergey A.1 (AUTHOR) sa-yakimov@yandex.ru, Toporova, Victoria A.1 (AUTHOR) toporova.viktorija@gmail.com, Kirpichnikov, Mikhail P.1,2 (AUTHOR) kirpichnikov@inbox.ru, Nekrasova, Oksana V.1 (AUTHOR) avfeofanov@yandex.ru, Feofanov, Alexey V.1,2 (AUTHOR)
Publikováno v:
Membranes. Jul2023, Vol. 13 Issue 7, p645. 18p.