BDD-X Dataset Papers With Code
4.7 (717) · € 62.99 · En stock
Berkeley Deep Drive-X (eXplanation) is a dataset is composed of over 77 hours of driving within 6,970 videos. The videos are taken in diverse driving conditions, e.g. day/night, highway/city/countryside, summer/winter etc. On average 40 seconds long, each video contains around 3-4 actions, e.g. speeding up, slowing down, turning right etc., all of which are annotated with a description and an explanation. Our dataset contains over 26K activities in over 8.4M frames.
Exploring the Berkeley Deep Drive Autonomous Vehicle Dataset, by Jimmy Guerrero, Voxel51
PDF] Local Interpretations for Explainable Natural Language Processing: A Survey
Evaluation of Detection and Segmentation Tasks on Driving Datasets
BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning
J. Imaging, Free Full-Text
Towards Knowledge-driven Autonomous Driving
Electronics, Free Full-Text
Exploring the Berkeley Deep Drive Autonomous Vehicle Dataset, by Jimmy Guerrero, Voxel51
BDD100K: A Large-scale Diverse Driving Video Database – The Berkeley Artificial Intelligence Research Blog
LLMs in Autonomous Driving — Part 3, by Isaac Kargar, Feb, 2024
