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- Chinese University of Hong KongHK59 papers
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- Chinese Academy of SciencesCN11 papers
- The University of SydneyAU9 papers
- University of Hong KongHK9 papers
- Beihang UniversityCN8 papers
- Nanyang Technological UniversitySG8 papers
- Shanghai Jiao Tong UniversityCN7 papers
- Shenzhen Institutes of Advanced TechnologyCN7 papers
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26 papers · 1 filter
Quantum Differentially Private Sparse Regression Learning
Yuxuan Du, Min-Hsiu Hsieh, Tongliang Liu +2
The eligibility of various advanced quantum algorithms will be questioned if they can not guarantee privacy. To fill this knowledge gap, here we devise an efficient quantum differe…
Thinking in Frequency: Face Forgery Detection by Mining Frequency-aware Clues
Yuyang Qian, Guojun Yin, Lu Sheng +2
As realistic facial manipulation technologies have achieved remarkable progress, social concerns about potential malicious abuse of these technologies bring out an emerging researc…
Continual Representation Learning for Biometric Identification
Bo Zhao, Shixiang Tang, Dapeng Chen +2
With the explosion of digital data in recent years, continuously learning new tasks from a stream of data without forgetting previously acquired knowledge has become increasingly i…
3D Human Mesh Regression with Dense Correspondence
Wang Zeng, Wanli Ouyang, Ping Luo +2
Estimating 3D mesh of the human body from a single 2D image is an important task with many applications such as augmented reality and Human-Robot interaction. However, prior works…
ECoPANN: A Framework for Estimating Cosmological Parameters using Artificial Neural Networks
Guo-Jian Wang, Si-Yao Li, Jun-Qing Xia
In this work, we present a new method to estimate cosmological parameters accurately based on the artificial neural network (ANN), and a code called ECoPANN (Estimating Cosmologica…
TPNet: Trajectory Proposal Network for Motion Prediction
Liangji Fang, Qinhong Jiang, Jianping Shi +1
Making accurate motion prediction of the surrounding traffic agents such as pedestrians, vehicles, and cyclists is crucial for autonomous driving. Recent data-driven motion predict…