2 citations · 2 across the 5 of their papers we have counts for
5 papers
Reconstructing Deep Neural Networks: Unleashing the Optimization Potential of Natural Gradient Descent
Weihua Liu, Said Boumaraf, Jianwu Li +4
Natural gradient descent (NGD) is a powerful optimization technique for machine learning, but the computational complexity of the inverse Fisher information matrix limits its appli…
BENet: A Cross-domain Robust Network for Detecting Face Forgeries via Bias Expansion and Latent-space Attention
Weihua Liu, Jianhua Qiu, Said Boumaraf +5
In response to the growing threat of deepfake technology, we introduce BENet, a Cross-Domain Robust Bias Expansion Network. BENet enhances the detection of fake faces by addressing…
Cross-domain Robust Deepfake Bias Expansion Network for Face Forgery Detection
Weihua Liu, Lin Li, Chaochao Lin +1
The rapid advancement of deepfake technologies raises significant concerns about the security of face recognition systems. While existing methods leverage the clues left by deepfak…
Dynamic Multi-Domain Knowledge Networks for Chest X-ray Report Generation
Weihua Liu, Youyuan Xue, Chaochao Lin +1
The automated generation of radiology diagnostic reports helps radiologists make timely and accurate diagnostic decisions while also enhancing clinical diagnostic efficiency. Howev…
Occlusion-Aware Deep Convolutional Neural Network via Homogeneous Tanh-transforms for Face Parsing
Jianhua Qiua, Weihua Liu, Chaochao Lin +3
Face parsing infers a pixel-wise label map for each semantic facial component. Previous methods generally work well for uncovered faces, however, they overlook facial occlusion and…