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객체 검출 성능 향상을 위한 RepPoints 기반 IoU Supervision
김근호(Kun-Ho Kim),김민재(Min-jae Kim),김형태(Hyungtae Kim),박석목(Seokmok Park),박혁진(Hyeokjin Park),성현오(Hyunoh Sung),백준기(JoonKi Paik) 대한전자공학회 2021 대한전자공학회 학술대회 Vol.2021 No.6
RepPoints (Representative Points) recently showed that the anchor-free object detector could achieve competitive performance due to the adaptive representation. In this paper, we improve the representation power of RepPoints through the Intersection-over-Union (IoU) supervision. By adding the IoU estimation branch and loss, the network can learn to move the RepPoints toward more semantic locations. After training, the estimated IoU value is also used as the localization confidence in the Non-Maximum-Suppression (NMS) stage. Experimental results show that the proposed method is more accurate than the existing methods.