Gatedip/GDIP-Yolo
Gated Differentiable Image Processing (GDIP) for Object Detection in Adverse Conditions | Accepted at ICRA 2023
This project helps autonomous vehicles and surveillance systems reliably identify objects in challenging conditions like fog or low light. It takes regular camera footage as input and outputs improved object detection accuracy, pinpointing objects that might otherwise be missed. This is for engineers and researchers developing robust computer vision systems for real-world deployment.
No commits in the last 6 months.
Use this if you need to improve the performance of object detection systems on images captured in adverse weather or poor lighting.
Not ideal if you need full control over the training process, as the training script is not yet publicly available.
Stars
65
Forks
7
Language
Python
License
MIT
Category
Last pushed
Jan 17, 2023
Commits (30d)
0
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