Ambiguity-Resistant Semi-Supervised Learning for Dense Object Detection

Author:

Liu Chang1,Zhang Weiming2,Lin Xiangru2,Zhang Wei2,Tan Xiao2,Han Junyu2,Li Xiaomao1,Ding Errui2,Wang Jingdong2

Affiliation:

1. Shanghai University

2. Baidu Inc

Funder

National Natural Science Foundation of China

Publisher

IEEE

Reference37 articles.

1. Pseco: Pseudo labeling and consistency training for semi-supervised object detection;li;European Conference on Computer Vision,0

2. VarifocalNet: An IoU-aware Dense Object Detector

3. Dtg-ssod: Dense teacher guidance for semi-supervised object detection;li;ArXiv Preprint,2022

4. Interactive Self-Training with Mean Teachers for Semi-supervised Object Detection

5. Generalized focal loss: Learning qualified and distributed bounding boxes for dense object detection;li;Advances in neural information processing systems,2020

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