16 citations · 30 across the 31 of their papers we have counts for
6 papers · 1 filter
FontGuard: A Robust Font Watermarking Approach Leveraging Deep Font Knowledge
Kahim Wong, Jicheng Zhou, Kemou Li +3
The proliferation of AI-generated content brings significant concerns on the forensic and security issues such as source tracing, copyright protection, etc, highlighting the need f…
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…
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…
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…