581 citations · 591 across the 5 of their papers we have counts for
5 papers
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…
R-Cut: Enhancing Explainability in Vision Transformers with Relationship Weighted Out and Cut
Yingjie Niu, Ming Ding, Maoning Ge +3
Transformer-based models have gained popularity in the field of natural language processing (NLP) and are extensively utilized in computer vision tasks and multi-modal models such…
RSG-Net: Towards Rich Sematic Relationship Prediction for Intelligent Vehicle in Complex Environments
Yafu Tian, Alexander Carballo, Ruifeng Li +1
Behavioral and semantic relationships play a vital role on intelligent self-driving vehicles and ADAS systems. Different from other research focused on trajectory, position, and bo…
Perception and Sensing for Autonomous Vehicles Under Adverse Weather Conditions: A Survey
Yuxiao Zhang, Alexander Carballo, Hanting Yang +1
Automated Driving Systems (ADS) open up a new domain for the automotive industry and offer new possibilities for future transportation with higher efficiency and comfortable experi…
Learning a Model for Inferring a Spatial Road Lane Network Graph using Self-Supervision
Robin Karlsson, David Robert Wong, Simon Thompson +1
Interconnected road lanes are a central concept for navigating urban roads. Currently, most autonomous vehicles rely on preconstructed lane maps as designing an algorithmic model i…