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.

Semantic Segmentation

Evaluation of Detection and Segmentation Tasks on Driving Datasets

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

BDD100K val Benchmark (Object Detection)

ContrXT: Generating contrastive explanations from any text classifier - ScienceDirect

Machine Learning Datasets

Electronics, Free Full-Text

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

BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning

The comparison with ComboGAN and StarGAN on BDD validation dataset