BDD-X Dataset Papers With Code

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.

PDF] Zero-Suppressed BDDs for Set Manipulation in Combinatorial Problems

PDF] Zero-Suppressed BDDs for Set Manipulation in Combinatorial Problems

Evaluation of Detection and Segmentation Tasks on Driving Datasets

Binary decision diagram - Wikipedia

Machine Learning Datasets

Exploring the Berkeley Deep Drive Autonomous Vehicle Dataset, by Jimmy Guerrero, Voxel51

BDD-X Dataset Papers With Code

BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning

DDI-100 Dataset Papers With Code

Towards Knowledge-driven Autonomous Driving

J. Imaging, Free Full-Text

Rank2Tell: A Multimodal Driving Dataset for Joint Importance Ranking and Reasoning