Heterogeneous graph-based trajectory prediction using local map context and social interactions
Precisely predicting the future trajectories of surrounding traffic participants is a crucial but
challenging problem in autonomous driving, due to complex interactions between traffic …
challenging problem in autonomous driving, due to complex interactions between traffic …
Wolf: Captioning Everything with a World Summarization Framework
B Li, L Zhu, R Tian, S Tan, Y Chen, Y Lu, Y Cui… - arXiv preprint arXiv …, 2024 - arxiv.org
We propose Wolf, a WOrLd summarization Framework for accurate video captioning. Wolf is
an automated captioning framework that adopts a mixture-of-experts approach, leveraging …
an automated captioning framework that adopts a mixture-of-experts approach, leveraging …
SemanticFormer: Holistic and Semantic Traffic Scene Representation for Trajectory Prediction using Knowledge Graphs
Trajectory prediction in autonomous driving relies on accurate representation of all relevant
contexts of the driving scene including traffic participants, road topology, traffic signs as well …
contexts of the driving scene including traffic participants, road topology, traffic signs as well …
Generation of Training Data from HD Maps in the Lanelet2 Framework
Using HD maps directly as training data for machine learning tasks has seen a massive
surge in popularity and shown promising results, eg in the field of map perception. Despite …
surge in popularity and shown promising results, eg in the field of map perception. Despite …