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.

GitHub - microsoft/X-Decoder: [CVPR 2023] Official Implementation of X-Decoder for generalized decoding for pixel, image and language

2022-8-7 arXiv roundup: Adam and sharpness, Recursive self-improvement for coding, Training and model tweaks

BDD-X Dataset Papers With Code

DWD Dataset Papers With Code

Artificial Intelligence (Subject Code - 843) : General Instructions

Sensors, Free Full-Text

BDD100K: A Large-scale Diverse Driving Video Database – The Berkeley Artificial Intelligence Research Blog

GitHub - microsoft/X-Decoder: [CVPR 2023] Official Implementation of X-Decoder for generalized decoding for pixel, image and language

Binary decision diagram - Wikipedia

HDD Dataset Papers With Code

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

BDD100K Dataset Papers With Code

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

PDF] Local Interpretations for Explainable Natural Language Processing: A Survey