Delving into Multi-modal Multi-task Foundation Models for Road Scene Understanding: From Learning Paradigm Perspectives
Foundation models have indeed made a profound impact on various fields, emerging as
pivotal components that significantly shape the capabilities of intelligent systems. In the …
pivotal components that significantly shape the capabilities of intelligent systems. In the …
Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability
World models can foresee the outcomes of different actions, which is of paramount
importance for autonomous driving. Nevertheless, existing driving world models still have …
importance for autonomous driving. Nevertheless, existing driving world models still have …
Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving
Autonomous driving has advanced significantly due to sensors, machine learning, and
artificial intelligence improvements. However, prevailing methods struggle with intricate …
artificial intelligence improvements. However, prevailing methods struggle with intricate …
SciQu: Accelerating Materials Properties Prediction with Automated Literature Mining for Self-Driving Laboratories
A Babu - arXiv preprint arXiv:2407.08270, 2024 - arxiv.org
Assessing different material properties to predict specific attributes, such as band gap,
resistivity, young modulus, work function, and refractive index, is a fundamental requirement …
resistivity, young modulus, work function, and refractive index, is a fundamental requirement …
[PDF][PDF] Generalized Predictive Model for Autonomous Driving Supplementary Material
Video is a particularly universal and scalable target given a wealth of uncalibrated driving
videos. Different from BEV representations [25, 37] that require camera extrinsic parameters …
videos. Different from BEV representations [25, 37] that require camera extrinsic parameters …