17 citations · 39 across the 18 of their papers we have counts for
18 papers
RLMiniStyler: Light-weight RL Style Agent for Arbitrary Sequential Neural Style Generation
Jing Hu, Chengming Feng, Shu Hu +4
Arbitrary style transfer aims to apply the style of any given artistic image to another content image. Still, existing deep learning-based methods often require significant computa…
A Self-Learning Multimodal Approach for Fake News Detection
Hao Chen, Hui Guo, Baochen Hu +5
The rapid growth of social media has resulted in an explosion of online news content, leading to a significant increase in the spread of misleading or false information. While mach…
An Explainable Non-local Network for COVID-19 Diagnosis
Jingfu Yang, Peng Huang, Jing Hu +5
The CNN has achieved excellent results in the automatic classification of medical images. In this study, we propose a novel deep residual 3D attention non-local network (NL-RAN) to…
Robustly Optimized Deep Feature Decoupling Network for Fatty Liver Diseases Detection
Peng Huang, Shu Hu, Bo Peng +3
Current medical image classification efforts mainly aim for higher average performance, often neglecting the balance between different classes. This can lead to significant differe…
Masked Conditional Diffusion Model for Enhancing Deepfake Detection
Tiewen Chen, Shanmin Yang, Shu Hu +4
Recent studies on deepfake detection have achieved promising results when training and testing faces are from the same dataset. However, their results severely degrade when confron…
Efficient Image Super-Resolution via Symmetric Visual Attention Network
Chengxu Wu, Qinrui Fan, Shu Hu +3
An important development direction in the Single-Image Super-Resolution (SISR) algorithms is to improve the efficiency of the algorithms. Recently, efficient Super-Resolution (SR)…
UMedNeRF: Uncertainty-aware Single View Volumetric Rendering for Medical Neural Radiance Fields
Jing Hu, Qinrui Fan, Shu Hu +3
In the field of clinical medicine, computed tomography (CT) is an effective medical imaging modality for the diagnosis of various pathologies. Compared with X-ray images, CT images…
X-Transfer: A Transfer Learning-Based Framework for GAN-Generated Fake Image Detection
Lei Zhang, Hao Chen, Shu Hu +5
Generative adversarial networks (GANs) have remarkably advanced in diverse domains, especially image generation and editing. However, the misuse of GANs for generating deceptive im…
CrossDF: Improving Cross-Domain Deepfake Detection with Deep Information Decomposition
Shanmin Yang, Hui Guo, Shu Hu +5
Deepfake technology poses a significant threat to security and social trust. Although existing detection methods have shown high performance in identifying forgeries within dataset…
Controlling Neural Style Transfer with Deep Reinforcement Learning
Chengming Feng, Jing Hu, Xin Wang +5
Controlling the degree of stylization in the Neural Style Transfer (NST) is a little tricky since it usually needs hand-engineering on hyper-parameters. In this paper, we propose t…
RL-I2IT: Image-to-Image Translation with Deep Reinforcement Learning
Jing Hu, Ziwei Luo, Chengming Feng +7
Most existing Image-to-Image Translation (I2IT) methods generate images in a single run of a deep learning (DL) model. However, designing such a single-step model is always challen…
Harnessing the Power of Text-image Contrastive Models for Automatic Detection of Online Misinformation
Hao Chen, Peng Zheng, Xin Wang +5
As growing usage of social media websites in the recent decades, the amount of news articles spreading online rapidly, resulting in an unprecedented scale of potentially fraudulent…
Attacking Important Pixels for Anchor-free Detectors
Yunxu Xie, Shu Hu, Xin Wang +4
Deep neural networks have been demonstrated to be vulnerable to adversarial attacks: subtle perturbation can completely change the prediction result. Existing adversarial attacks o…
Detection of Real-time DeepFakes in Video Conferencing with Active Probing and Corneal Reflection
Hui Guo, Xin Wang, Siwei Lyu
The COVID pandemic has led to the wide adoption of online video calls in recent years. However, the increasing reliance on video calls provides opportunities for new impersonation…
RMBench: Benchmarking Deep Reinforcement Learning for Robotic Manipulator Control
Yanfei Xiang, Xin Wang, Shu Hu +4
Reinforcement learning is applied to solve actual complex tasks from high-dimensional, sensory inputs. The last decade has developed a long list of reinforcement learning algorithm…
Rank-based Decomposable Losses in Machine Learning: A Survey
Shu Hu, Xin Wang, Siwei Lyu
Recent works have revealed an essential paradigm in designing loss functions that differentiate individual losses vs. aggregate losses. The individual loss measures the quality of…
Open-Eye: An Open Platform to Study Human Performance on Identifying AI-Synthesized Faces
Hui Guo, Shu Hu, Xin Wang +2
AI-synthesized faces are visually challenging to discern from real ones. They have been used as profile images for fake social media accounts, which leads to high negative social i…
GAN-generated Faces Detection: A Survey and New Perspectives
Xin Wang, Hui Guo, Shu Hu +2
Generative Adversarial Networks (GAN) have led to the generation of very realistic face images, which have been used in fake social media accounts and other disinformation matters…