Vehicle-Oriented Intelligence with Data.
We fill the void in autonomous driving research.
Building AI systems for next-generation autonomous mobility.
End-to-end intelligent systems — from perception to planning and decision-making in complex real-world environments.
Deep learning-based scene understanding, object detection, tracking, and semantic segmentation for camera and LiDAR.
Combining camera, LiDAR, and radar to build robust, weather-resilient perception pipelines for autonomous vehicles.
High-definition map construction, lane-level road marking mapping, and simultaneous localization and mapping.
VLM-based reasoning for enhanced autonomous driving map construction and pedestrian safety analysis.
Synthetic data generation using diffusion models and dataset curation pipelines for autonomous driving.
Recognition received by VOID Lab members in competitions and research programs.
