Killing two birds with one stone: Efficient and robust training of face recognition cnns by partial fc

X An, J Deng, J Guo, Z Feng, XH Zhu… - Proceedings of the …, 2022 - openaccess.thecvf.com
Learning discriminative deep feature embeddings by using million-scale in-the-wild datasets
and margin-based softmax loss is the current state-of-the-art approach for face recognition …
被引用次数：72 相关文章

Killing Two Birds with One Stone: Efficient and Robust Training of Face Recognition CNNs by Partial FC

X An, J Deng, J Guo, Z Feng, XH Zhu… - 2022 IEEE/CVF …, 2022 - ieeexplore.ieee.org
Learning discriminative deep feature embeddings by using million-scale in-the-wild datasets
and margin-based softmax loss is the current state-of-the-art approach for face recognition …

Killing Two Birds with One Stone: Efficient and Robust Training of Face Recognition CNNs by Partial FC

X An, J Deng, J Guo, Z Feng, X Zhu, J Yang… - arXiv preprint arXiv …, 2022 - arxiv.org
Learning discriminative deep feature embeddings by using million-scale in-the-wild datasets
and margin-based softmax loss is the current state-of-the-art approach for face recognition …

Killing Two Birds with One Stone: Efficient and Robust Training of Face Recognition CNNs by Partial FC

X An, J Deng, J Guo, Z Feng, XH Zhu… - 2022 IEEE/CVF …, 2022 - computer.org
Learning discriminative deep feature embeddings by using million-scale in-the-wild datasets
and margin-based softmax loss is the current state-of-the-art approach for face recognition …

Killing Two Birds with One Stone: Efficient and Robust Training of Face Recognition CNNs by Partial FC

X An, J Deng, J Guo, Z Feng, X Zhu, J Yang… - arXiv e …, 2022 - ui.adsabs.harvard.edu
Learning discriminative deep feature embeddings by using million-scale in-the-wild datasets
and margin-based softmax loss is the current state-of-the-art approach for face recognition …