Details

Autor(en) / Beteiligte

• Pham, Hieu
• Dai, Zihang
• Xie, Qizhe
• Le, Quoc V.

Titel

Meta Pseudo Labels

Ist Teil von

• 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021, p.11552-11563

Ort / Verlag

IEEE

Erscheinungsjahr

2021

Link zum Volltext

• Volltext

Quelle

IEEE Xplore

Beschreibungen/Notizen

• We present Meta Pseudo Labels, a semi-supervised learning method that achieves a new state-of-the-art top-1 accuracy of 90.2% on ImageNet, which is 1.6% better than the existing state-of-the-art [16]. Like Pseudo Labels, Meta Pseudo Labels has a teacher network to generate pseudo labels on unlabeled data to teach a student network. However, unlike Pseudo Labels where the teacher is fixed, the teacher in Meta Pseudo Labels is constantly adapted by the feedback of the student's performance on the labeled dataset. As a result, the teacher generates better pseudo labels to teach the student. 1