6 papers
ExpFace: Exponential Angular Margin Loss for Deep Face Recognition
Jinhui Zheng, Xueyuan Gong
Face recognition is an open-set problem requiring high discriminative power to ensure that intra-class distances remain smaller than inter-class distances. Margin-based softmax los…
AttFC: Attention Fully-Connected Layer for Large-Scale Face Recognition with One GPU
Zhuowen Zheng, Yain-Whar Si, Xiaochen Yuan +5
Nowadays, with the advancement of deep neural networks (DNNs) and the availability of large-scale datasets, the face recognition (FR) model has achieved exceptional performance. Ho…
MSConv: Multiplicative and Subtractive Convolution for Face Recognition
Si Zhou, Yain-Whar Si, Xiaochen Yuan +5
In Neural Networks, there are various methods of feature fusion. Different strategies can significantly affect the effectiveness of feature representation, consequently influencing…
AdaSin: Enhancing Hard Sample Metrics with Dual Adaptive Penalty for Face Recognition
Qiqi Guo, Zhuowen Zheng, Guanghua Yang +5
In recent years, the emergence of deep convolutional neural networks has positioned face recognition as a prominent research focus in computer vision. Traditional loss functions, s…
RVAFM: Re-parameterizing Vertical Attention Fusion Module for Handwritten Paragraph Text Recognition
Jinhui Zheng, Zhiquan Liu, Yain-Whar Si +5
Handwritten Paragraph Text Recognition (HPTR) is a challenging task in Computer Vision, requiring the transformation of a paragraph text image, rich in handwritten text, into text…
FastFace: Fast-converging Scheduler for Large-scale Face Recognition Training with One GPU
Xueyuan Gong, Zhiquan Liu, Yain-Whar Si +5
Computing power has evolved into a foundational and indispensable resource in the area of deep learning, particularly in tasks such as Face Recognition (FR) model training on large…