BDD-X Dataset Papers With Code
Por un escritor de hombre misterioso
Descripción
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.
LLMs in Autonomous Driving — Part 3, by Isaac Kargar, Feb, 2024
How to Test Code Coupled to APIs or Databases
PDF] Zero-Suppressed BDDs for Set Manipulation in Combinatorial Problems
Object detection results of YOLO V3 on BDD dataset. Left to right
Exploring the Berkeley Deep Drive Autonomous Vehicle Dataset, by Jimmy Guerrero, Voxel51
Binary decision diagram - Wikipedia
every thing is given. if u dont know the answer dont
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
BDD100K val Benchmark (Semantic Segmentation)
BDD100K val Benchmark (Object Detection)
Exploring the Berkeley Deep Drive Autonomous Vehicle Dataset, by Jimmy Guerrero, Voxel51
Semantic Segmentation
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