Malik Mohrat — accepted AI-conference papers

2025

GSplatLoc: Grounding Keypoint Descriptors into 3D Gaussian Splatting for Improved Visual Localization

Gennady Sidorov, Malik Mohrat, Denis Gridusov, Ruslan Rakhimov, Sergey A. Kolyubin

IROS 2025

Visual localization methods often present a trade-off between the high efficiency of specialized approaches, such as scene coordinate regression, and the need for rich, versatile scene representations for broader robotics tasks. To bridge this gap, we explore the use of 3D Gaussian Splatting (3DGS),

Cited by 14 Source ↗code ↗Scholar ↗

2023

Geometrically Consistent Monocular Metric-Semantic 3D Mapping for Indoor Environments with Transparent and Reflecting Objects

Malik Mohrat, Amiran Berkaev, Alexey Burkov, Sergey Kolyubin

IROS 2023poster

3D mapping is crucial for many applications in robotics and related industries. To build dense high-quality point clouds accurate depth estimation or completion is needed. This paper presents the development of a metric-semantic mapping pipeline based on Deep Neural Networks (DNN) which assures geom…

Cited by 0 Source ↗Scholar ↗