Search Results for author: Hang Du

Found 7 papers, 2 papers with code

Multi-Agent Semi-Siamese Training for Long-tail and Shallow Face Learning

no code implementations10 May 2021 Hailin Shi, Dan Zeng, Yichun Tai, Hang Du, Yibo Hu, Tao Mei

However, unlike the existing public face datasets, in many real-world scenarios of face recognition, the depth of training dataset is shallow, which means only two face images are available for each ID.

Face Recognition

Boosting Semi-Supervised Face Recognition with Noise Robustness

1 code implementation10 May 2021 Yuchi Liu, Hailin Shi, Hang Du, Rui Zhu, Jun Wang, Liang Zheng, Tao Mei

This paper presents an effective solution to semi-supervised face recognition that is robust to the label noise aroused by the auto-labelling.

Face Recognition

Towards NIR-VIS Masked Face Recognition

no code implementations14 Apr 2021 Hang Du, Hailin Shi, Yinglu Liu, Dan Zeng, Tao Mei

In this paper, we aim to address the challenge of NIR-VIS masked face recognition from the perspectives of training data and training method.

3D Face Reconstruction Face Recognition +1

Scene Text Detection with Selected Anchor

no code implementations19 Aug 2020 Anna Zhu, Hang Du, Shengwu Xiong

Object proposal technique with dense anchoring scheme for scene text detection were applied frequently to achieve high recall.

Region Proposal Scene Text Detection

NPCFace: Negative-Positive Collaborative Training for Large-scale Face Recognition

no code implementations20 Jul 2020 Dan Zeng, Hailin Shi, Hang Du, Jun Wang, Zhen Lei, Tao Mei

However, the correlation between hard positive and hard negative is overlooked, and so is the relation between the margins in positive and negative logits.

Face Recognition

Semi-Siamese Training for Shallow Face Learning

2 code implementations ECCV 2020 Hang Du, Hailin Shi, Yuchi Liu, Jun Wang, Zhen Lei, Dan Zeng, Tao Mei

Extensive experiments on various benchmarks of face recognition show the proposed method significantly improves the training, not only in shallow face learning, but also for conventional deep face data.

Face Recognition

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