Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Rakhimov, Ruslan"'
Although various visual localization approaches exist, such as scene coordinate and pose regression, these methods often struggle with high memory consumption or extensive optimization requirements. To address these challenges, we utilize recent adva
Externí odkaz:
http://arxiv.org/abs/2409.16502
Publikováno v:
in IEEE Access, vol. 11, pp. 95681-95691, 2023
We present an approach for the reconstruction of textured 3D meshes of human heads from one or few views. Since such few-shot reconstruction is underconstrained, it requires prior knowledge which is hard to impose on traditional 3D reconstruction alg
Externí odkaz:
http://arxiv.org/abs/2209.04436
We present a new system (NPBG++) for the novel view synthesis (NVS) task that achieves high rendering realism with low scene fitting time. Our method efficiently leverages the multiview observations and the point cloud of a static scene to predict a
Externí odkaz:
http://arxiv.org/abs/2203.13318
Autor:
Voynov, Oleg, Bobrovskikh, Gleb, Karpyshev, Pavel, Galochkin, Saveliy, Ardelean, Andrei-Timotei, Bozhenko, Arseniy, Karmanova, Ekaterina, Kopanev, Pavel, Labutin-Rymsho, Yaroslav, Rakhimov, Ruslan, Safin, Aleksandr, Serpiva, Valerii, Artemov, Alexey, Burnaev, Evgeny, Tsetserukou, Dzmitry, Zorin, Denis
We present a new multi-sensor dataset for multi-view 3D surface reconstruction. It includes registered RGB and depth data from sensors of different resolutions and modalities: smartphones, Intel RealSense, Microsoft Kinect, industrial cameras, and st
Externí odkaz:
http://arxiv.org/abs/2203.06111
Autor:
Matveev, Albert, Rakhimov, Ruslan, Artemov, Alexey, Bobrovskikh, Gleb, Egiazarian, Vage, Bogomolov, Emil, Panozzo, Daniele, Zorin, Denis, Burnaev, Evgeny
We propose Deep Estimators of Features (DEFs), a learning-based framework for predicting sharp geometric features in sampled 3D shapes. Differently from existing data-driven methods, which reduce this problem to feature classification, we propose to
Externí odkaz:
http://arxiv.org/abs/2011.15081
Autor:
Rakhimov, Ruslan, Bogomolov, Emil, Notchenko, Alexandr, Mao, Fung, Artemov, Alexey, Zorin, Denis, Burnaev, Evgeny
DensePose estimation task is a significant step forward for enhancing user experience computer vision applications ranging from augmented reality to cloth fitting. Existing neural network models capable of solving this task are heavily parameterized
Externí odkaz:
http://arxiv.org/abs/2006.15190
The video generation task can be formulated as a prediction of future video frames given some past frames. Recent generative models for videos face the problem of high computational requirements. Some models require up to 512 Tensor Processing Units
Externí odkaz:
http://arxiv.org/abs/2006.10704
Autor:
Lukpanov, Rauan, Yenkebaev, Serik, Zhantlessova, Zhibek, Dyussembinov, Duman, Altynbekova, Aliya, Rakhimov, Ruslan
Publikováno v:
Eastern-European Journal of Enterprise Technologies; 2024, Vol. 128 Issue 1, p6-13, 8p
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