did=401 task=did=401 YACVID - Berkeley DeepDrive Video - Details

Yet Another Computer Vision Index To Datasets (YACVID) - Details

Stand: 2024-03-19 04:50:03 - Overview

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Name (Institute + Shorttitle)Berkeley DeepDrive Video  
Description (include details on usage, files and paper references)The Berkeley DeepDrive Video Dataset contains 2x order of magnitude more video training data.


Explore 100,000 HD video sequences of over 1,100-hour driving experience across many different times in the day, weather conditions, and driving scenarios. Our video sequences also include GPS locations, IMU data, and timestamps.


Road Object Detection
2D Bounding Boxes annotated on 100,000 images for bus, traffic light, traffic sign, person, bike, truck, motor, car, train, and rider.

Instance Segmentation
Explore over 10,000 diverse images with pixel-level and rich instance-level annotations.
training (3,683 images), validation (500 images), and testing (1,500 images) in 40 classes (5683)


Driveable Area
Learn complicated drivable decision from 100,000 images.

Lane Markings
Multiple types of lane marking annotations on 100,000 images for driving guidance.




https://arxiv.org/pdf/1805.04687.pdf
 
URL Linkhttps://github.com/gy20073/BDD_Driving_Model/ 
Files (#)100000 
References (SKIPPED)
Category (SKIPPED) 
Tags (single words, spaced)urban autonomous driving deep learning endtoend 
Last Changed2024-03-19 
Turing (2.12+3.25=?) :-)