Proceedings of the Korea Information Processing Society Conference (한국정보처리학회:학술대회논문집)
- 2020.05a
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- Pages.595-598
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- 2020
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- 2005-0011(pISSN)
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- 2671-7298(eISSN)
DOI QR Code
A Study on the Optimization of IoU
IoU의 최적화에 관한 연구
Abstract
IoU (Intersection over Union) is the most commonly used index in target detection. The core requirement of target detection is what is in the image and where. Based on these two problems, classification training and positional regression training are needed. However, in the process of position regression, the most commonly used method is to obtain the IoU of the predicted bounding box and ground-truth bounding box. Calculating bounding box regression losses should take into account three important geometric measures, namely the overlap area, the distance, and the aspect ratio. Although GIoU (Generalized Intersection over Union) improves the calculation function of image overlap degree, it still can't represent the distance and aspect ratio of the graph well. As a result of technological progress, Bounding-Box is no longer represented by coordinates x,y,w and h of four positions. Therefore, the IoU can be further optimized with the center point and aspect ratio of Bounding-Box.
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