Demo Data from EDBT 2026 / reviewers in the wild / expert
Yaroslav Labutin-Rymsho
dblp:315/9440
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Geometric modeling and processing
3d reconstruction |
0.7 | 1 | 2023 | Multi-Sensor Large-Scale Dataset for Multi-View 3D Reconstruction · CVPR 2023 |
Computational photography and imaging › image-based modeling
3d reconstruction from images |
0.7 | 1 | 2023 | Multi-Sensor Large-Scale Dataset for Multi-View 3D Reconstruction · CVPR 2023 |
Computational photography and imaging
multi-sensor imaging |
0.2 | 1 | 2023 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Multi-Sensor Large-Scale Dataset for Multi-View 3D ReconstructionabstractWe 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 |
CVPR | 9 |