A technique has been developed to improve object detection in crowded scenes without retraining the model. This method adjusts the confidence threshold dynamically based on the size of the detected object and the overall score distribution within a frame. By lowering the initial threshold to capture more potential detections and then applying a three-layer filter, including checks on pose keypoints, the system can identify smaller or more distant objects that would typically be missed. AI
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IMPACT Offers a method to enhance object detection in challenging scenarios without the computational cost of retraining.
RANK_REASON The article describes a novel technique for improving object detection performance by modifying the post-processing of model outputs rather than retraining the model itself. [lever_c_demoted from research: ic=1 ai=1.0]
