vita-epfl/detection-attributes-fields
PyTorch implementation of "Detecting 32 Pedestrian Attributes for Autonomous Vehicles"
This tool helps autonomous vehicle developers analyze traffic scenes by identifying pedestrians and recognizing 32 distinct attributes about them from camera images. It takes raw image data as input and outputs bounding boxes around pedestrians along with detailed information about their appearance and behavior, including whether they are likely to cross the road. This is designed for engineers and researchers working on perception systems for self-driving cars.
No commits in the last 6 months.
Use this if you need to precisely detect pedestrians and understand their characteristics and potential actions for autonomous driving applications.
Not ideal if you are looking for a general-purpose object detection tool not specifically focused on detailed pedestrian analysis for autonomous vehicles.
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Language
Python
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Last pushed
Oct 16, 2021
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