Cut Out
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Motivation, Objectives and Related Works
Motivation, Objectives and Related Works
Motivation
Motivation
Objectives
Objectives
Cutout, also first seen in YOLOv4.
Related Works
Related Works
Methods
Methods
Idea
Idea
Cutout simulates occlusion by adding randomly generated black boxes on top of your images.
This does two things:
It makes your model do better detecting objects that are occluded (located) behind other objects.
It encourages your model to learn more distinguishing features about each class of object.
For example, if you're trying to detect American flags, your model may hone in on the stars. By covering up the stars in some of the images, you force it to also learn about the stripes. And thus, its performance in detecting American flags does much better when they are flapping in the wind.
Experimental Results
Experimental Results
Dataset
Dataset
Metrics
Metrics
Experimental Results
Experimental Results
Ablations
Ablations
Key Takeaways
Key Takeaways
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