2 papers
cs.RO2025
VLAD: A VLM-Augmented Autonomous Driving Framework with Hierarchical Planning and Interpretable Decision Process
Cristian Gariboldi, Hayato Tokida, Ken Kinjo +2
Recent advancements in open-source Visual Language Models (VLMs) such as LLaVA, Qwen-VL, and Llama have catalyzed extensive research on their integration with diverse systems. The…
cs.CV2024
Sparse Prototype Network for Explainable Pedestrian Behavior Prediction
Yan Feng, Alexander Carballo, Kazuya Takeda
Predicting pedestrian behavior is challenging yet crucial for applications such as autonomous driving and smart city. Recent deep learning models have achieved remarkable performan…