1 citations · 2 across the 6 of their papers we have counts for
6 papers
MapFM: Foundation Model-Driven HD Mapping with Multi-Task Contextual Learning
Leonid Ivanov, Vasily Yuryev, Dmitry Yudin
In autonomous driving, high-definition (HD) maps and semantic maps in bird's-eye view (BEV) are essential for accurate localization, planning, and decision-making. This paper intro…
Talk2SAM: Text-Guided Semantic Enhancement for Complex-Shaped Object Segmentation
Luka Vetoshkin, Dmitry Yudin
Segmenting objects with complex shapes, such as wires, bicycles, or structural grids, remains a significant challenge for current segmentation models, including the Segment Anythin…
LEG-SLAM: Real-Time Language-Enhanced Gaussian Splatting for SLAM
Roman Titkov, Egor Zubkov, Dmitry Yudin +3
Modern Gaussian Splatting methods have proven highly effective for real-time photorealistic rendering of 3D scenes. However, integrating semantic information into this representati…
OFMPNet: Deep End-to-End Model for Occupancy and Flow Prediction in Urban Environment
Youshaa Murhij, Dmitry Yudin
The task of motion prediction is pivotal for autonomous driving systems, providing crucial data to choose a vehicle behavior strategy within its surroundings. Existing motion predi…
Interactive Semantic Map Representation for Skill-based Visual Object Navigation
Tatiana Zemskova, Aleksei Staroverov, Kirill Muravyev +2
Visual object navigation using learning methods is one of the key tasks in mobile robotics. This paper introduces a new representation of a scene semantic map formed during the emb…
SegmATRon: Embodied Adaptive Semantic Segmentation for Indoor Environment
Tatiana Zemskova, Margarita Kichik, Dmitry Yudin +2
This paper presents an adaptive transformer model named SegmATRon for embodied image semantic segmentation. Its distinctive feature is the adaptation of model weights during infere…