Publications (8)
Data-driven Software-based Power Estimation for Embedded Devices
Haoyu Wang, Xinyi Li, Ti Zhou +1
Energy measurement of computer devices, which are widely used in the Internet of Things (IoT), is an important yet challenging task. Most of these IoT devices lack ready-to-use har…
CPU frequency scheduling of real-time applications on embedded devices with temporal encoding-based deep reinforcement learning
Ti Zhou, Man Lin
Small devices are frequently used in IoT and smart-city applications to perform periodic dedicated tasks with soft deadlines. This work focuses on developing methods to derive effi…
AI-Generated Video Detection via Spatio-Temporal Anomaly Learning
Jianfa Bai, Man Lin, Gang Cao
The advancement of generation models has led to the emergence of highly realistic artificial intelligence (AI)-generated videos. Malicious users can easily create non-existent vide…
Black-Box Attack against GAN-Generated Image Detector with Contrastive Perturbation
Zijie Lou, Gang Cao, Man Lin
Visually realistic GAN-generated facial images raise obvious concerns on potential misuse. Many effective forensic algorithms have been developed to detect such synthetic images in…
Video Inpainting Localization with Contrastive Learning
Zijie Lou, Gang Cao, Man Lin
Deep video inpainting is typically used as malicious manipulation to remove important objects for creating fake videos. It is significant to identify the inpainted regions blindly.…
Energy-Efficient Computation with DVFS using Deep Reinforcement Learning for Multi-Task Systems in Edge Computing
Xinyi Li, Ti Zhou, Haoyu Wang +1
Finding an optimal energy-efficient policy that is adaptable to underlying edge devices while meeting deadlines for tasks has always been challenging. This research studies general…
Spatio-temporal Co-attention Fusion Network for Video Splicing Localization
Man Lin, Gang Cao, Zijie Lou
Digital video splicing has become easy and ubiquitous. Malicious users copy some regions of a video and paste them to another video for creating realistic forgeries. It is signific…
Trusted Video Inpainting Localization via Deep Attentive Noise Learning
Zijie Lou, Gang Cao, Man Lin
Digital video inpainting techniques have been substantially improved with deep learning in recent years. Although inpainting is originally designed to repair damaged areas, it can…