2 citations · 3 across the 6 of their papers we have counts for
6 papers
Collaborative Trajectory Prediction via Late Fusion
Nadya Abdel Madjid, Murad Mebrahtu, Zakhar Yagudin +5
Predicting future trajectories of surrounding traffic agents is critical for safe autonomous navigation and collision avoidance. Despite all advances in the trajectory forecasting…
EagleVision: A Multi-Task Benchmark for Cross-Domain Perception in High-Speed Autonomous Racing
Zakhar Yagudin, Murad Mebrahtu, Ren Jin +5
High-speed autonomous racing presents extreme perception challenges, including large relative velocities and substantial domain shifts from conventional urban-driving datasets. Exi…
VDT-Auto: End-to-end Autonomous Driving with VLM-Guided Diffusion Transformers
Ziang Guo, Konstantin Gubernatorov, Selamawit Asfaw +2
In autonomous driving, dynamic environment and corner cases pose significant challenges to the robustness of ego vehicle's decision-making. To address these challenges, commencing…
METDrive: Multi-modal End-to-end Autonomous Driving with Temporal Guidance
Ziang Guo, Xinhao Lin, Zakhar Yagudin +4
Multi-modal end-to-end autonomous driving has shown promising advancements in recent work. By embedding more modalities into end-to-end networks, the system's understanding of both…
FADet: A Multi-sensor 3D Object Detection Network based on Local Featured Attention
Ziang Guo, Zakhar Yagudin, Selamawit Asfaw +2
Camera, LiDAR and radar are common perception sensors for autonomous driving tasks. Robust prediction of 3D object detection is optimally based on the fusion of these sensors. To e…
VLM-Auto: VLM-based Autonomous Driving Assistant with Human-like Behavior and Understanding for Complex Road Scenes
Ziang Guo, Zakhar Yagudin, Artem Lykov +2
Recent research on Large Language Models for autonomous driving shows promise in planning and control. However, high computational demands and hallucinations still challenge accura…