Zobrazeno 1 - 10
of 104
pro vyhledávání: '"Kuznetsov, Alexandr A."'
Autor:
Zhang, Yunxiang, Kuznetsov, Alexandr, Jindal, Akshay, Chen, Kenneth, Sochenov, Anton, Kaplanyan, Anton, Sun, Qi
Neural image representations have recently emerged as a promising technique for storing, streaming, and rendering visual data. Coupled with learning-based workflows, these novel representations have demonstrated remarkable visual fidelity and memory
Externí odkaz:
http://arxiv.org/abs/2407.01866
Despite significant advances in algorithms and hardware, global illumination continues to be a challenge in the real-time domain. Time constraints often force developers to either compromise on the quality of global illumination or disregard it altog
Externí odkaz:
http://arxiv.org/abs/2406.07906
In the wake of many new ML-inspired approaches for reconstructing and representing high-quality 3D content, recent hybrid and explicitly learned representations exhibit promising performance and quality characteristics. However, their scaling to high
Externí odkaz:
http://arxiv.org/abs/2405.20067
Autor:
Kuznetsov, Alexandr, Poluyanenko, Nikolay, Frontoni, Emanuele, Kandiy, Sergey, Peliukh, Oleksandr
Publikováno v:
In Expert Systems With Applications 1 March 2024 237 Part C
We propose NeuMIP, a neural method for representing and rendering a variety of material appearances at different scales. Classical prefiltering (mipmapping) methods work well on simple material properties such as diffuse color, but fail to generalize
Externí odkaz:
http://arxiv.org/abs/2104.02789
Autor:
Zhu, Shilin, Xu, Zexiang, Sun, Tiancheng, Kuznetsov, Alexandr, Meyer, Mark, Jensen, Henrik Wann, Su, Hao, Ramamoorthi, Ravi
Although Monte Carlo path tracing is a simple and effective algorithm to synthesize photo-realistic images, it is often very slow to converge to noise-free results when involving complex global illumination. One of the most successful variance-reduct
Externí odkaz:
http://arxiv.org/abs/2010.01775
Akademický článek
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Akademický článek
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Publikováno v:
Open Computer Science, Vol 12, Iss 1, Pp 66-74 (2022)
This article discusses computing systems that operate in residue number systems (RNSs). The main direction of improving computer systems (CSs) is increasing the speed of implementation of arithmetic operations and the reliability of their functioning
Externí odkaz:
https://doaj.org/article/1eb14ac821f441939417a5afcef63a86
Autor:
Kuznetsov, Alexandr, Rajba, Stanislaw A., Veselska, Olga, Bagmut, Mykhaylo, Ziubina, Ruslana, Peshkova, Olga
Publikováno v:
In Procedia Computer Science 2022 207:2192-2201