jwchoi384/Gaussian_YOLOv3

Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomous Driving (ICCV, 2019)

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This system helps autonomous vehicles accurately and quickly detect objects like cars, pedestrians, and traffic signs in real-time video feeds. It takes live camera footage as input and outputs precise bounding box detections for various objects, even indicating the uncertainty of these detections. Autonomous driving engineers or researchers developing self-driving car systems would use this to improve their object recognition capabilities.

669 stars. No commits in the last 6 months.

Use this if you need a high-performance object detection system for autonomous driving applications that can process video streams rapidly and provide reliable localization of objects, along with an estimate of how certain those detections are.

Not ideal if your primary need is detecting objects in static images or if you require detection for a domain other than autonomous driving, as it's specifically tuned for vehicle-related scenarios.

autonomous-driving vehicle-perception object-detection real-time-vision robotics
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 25 / 25

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669

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Last pushed

Jul 19, 2020

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