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Yaroslav Labutin-Rymsho

dblp:315/9440 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Computational photography and imaging · 56% Geometric modeling and processing · 44%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Geometric modeling and processing
3d reconstruction
0.712023
Multi-Sensor Large-Scale Dataset for Multi-View 3D Reconstruction · CVPR 2023
Computational photography and imaging › image-based modeling
3d reconstruction from images
0.712023
Multi-Sensor Large-Scale Dataset for Multi-View 3D Reconstruction · CVPR 2023
Computational photography and imaging
multi-sensor imaging
0.212023
Multi-Sensor Large-Scale Dataset for Multi-View 3D Reconstruction · CVPR 2023

Methods — techniques the papers use, named apart from their topics

structured light scanning · 0.7depth sensing · 0.7
YearPublicationVenuePosition
2023 Multi-Sensor Large-Scale Dataset for Multi-View 3D Reconstruction
abstract
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 structured-light scanner. The scenes are selected to emphasize a diverse set of material properties challenging for existing algorithms. We provide around 1.4 million images of 107 different scenes acquired from 100 viewing directions under 14 lighting conditions. We expect our dataset will be useful for evaluation and training of 3D reconstruction algorithms and for related tasks. The dataset is available at skol tech3d. appliedai. tech.
Oleg Voynov, Gleb Bobrovskikh, Pavel A. Karpyshev, Saveliy Galochkin, Andrei-Timotei Ardelean, Arseniy Bozhenko, Ekaterina Karmanova, Pavel Kopanev, Yaroslav Labutin-Rymsho, Ruslan Rakhimov, Aleksandr Safin, Valerii Serpiva, Alexey Artemov, Evgeny Burnaev, Dzmitry Tsetserukou, Denis Zorin
CVPR9