3 papers
cs.CV2025
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…
cs.CV2024
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…
cs.CV2023
X2-Softmax: Margin Adaptive Loss Function for Face Recognition
Jiamu Xu, Xiaoxiang Liu, Xinyuan Zhang +5
Learning the discriminative features of different faces is an important task in face recognition. By extracting face features in neural networks, it becomes easy to measure the sim…