Hongda Qin

Foggy-Aware Teacher: An Unsupervised Domain Adaptive Learning Framework for Object Detection in Foggy Scenes

Unsupervised domain adaptation (UDA) is an effective scheme to improve the performance of an object detector in foggy scenes by adapting labeled normal images (source domain) to unlabeled foggy images (target domain). Existing methods leverage the Teacher-Student mutual learning framework, <italic x