@inproceedings{
liu2024two,
title={Two Teachers Are Better Than One: Semi-supervised Elliptical Object Detection by  Dual-Teacher Collaborative Guidance},
author={Yu Liu and Longhan Feng and Qi Jia and Zezheng Liu and Zihuang Cao},
booktitle={ACM Multimedia 2024},
year={2024},
url={https://openreview.net/forum?id=SRZFOWf3lN}
}
Elliptical Object Detection (EOD) is crucial yet challenging due to complex scenes and varying object characteristics. Existing methods often struggle with parameter configurations and lack adaptability in label-scarce scenarios. To address this, a new semi-supervised teacher-student framework, Dual-Teacher Collaborative Guidance (DTCG), is proposed, comprising a five-parameter teacher detector, a six-parameter teacher detector, and a student detector. This allows the two teachers, specializing in different regression approaches, to co-instruct the student within a unified model, preventing errors and enhancing performance. Additionally, a feature correlation module (FCM) highlights differences between teacher features and employs deformable convolution to select advantageous features for final parameter regression. A collaborative training strategy (CoT) updates the teachers asynchronously, breaking through training and performance bottlenecks. Extensive experiments conducted on two widely recognized datasets affirm the superior performance of our DTCG over other leading competitors across various semi-supervised scenarios. Notably, our method achieves a 5.61% higher performance than the second best method when utilizing only 10% annotated data.
Two Teachers Are Better Than One: Semi-supervised Elliptical Object Detection by  Dual-Teacher Collaborative Guidance
Yu Liu Longhan Feng Qi Jia Zezheng Liu Zihuang Cao