Detecting objects in high-resolution input is a well-known problem in computer vision. When a certain area of the frame is of interest, inference over the complete frame is unnecessary. There are two ways to solve this issue: In many ways, the first approach is difficult. Training a model with large input often requires larger backbones, making the overall model bulkier.
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