End-to-End Semi-Supervised Object Detection with Soft Teacher
Author:
Affiliation:
1. Huazhong University of Science and Technology
2. Microsoft
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9709627/9709628/09710144.pdf?arnumber=9710144
Reference36 articles.
1. Self-Training With Noisy Student Improves ImageNet Classification
2. Unsupervised data augmentation for consistency training;xie;NIPS,2020
3. Towards Human-Machine Cooperation: Self-Supervised Sample Mining for Object Detection
4. FCOS: Fully Convolutional One-Stage Object Detection
5. Rethinking pre-training and self-training;zoph;NIPS,2020
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