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.

BDD-X Dataset Papers With Code

Deriving YOLO anchor boxes - Convolutional Neural Networks - DeepLearning.AI

ContrXT: Generating contrastive explanations from any text classifier - ScienceDirect

BDD100K val Benchmark (Lane Detection)

Machine Learning Datasets

Artificial Intelligence (Subject Code - 843) : General Instructions

ContrXT: Generating contrastive explanations from any text classifier - ScienceDirect

LLMs in Autonomous Driving — Part 3, by Isaac Kargar, Feb, 2024

Number of nodes and code sizes for BDD machine and QDD machine.