20 citations · 23 across the 6 of their papers we have counts for
7 papers
A Real-Time Multi-Task Learning System for Joint Detection of Face, Facial Landmark and Head Pose
Qingtian Wu, Liming Zhang
Extreme head postures pose a common challenge across a spectrum of facial analysis tasks, including face detection, facial landmark detection (FLD), and head pose estimation (HPE).…
DeciLS-PBO: an Effective Local Search Method for Pseudo-Boolean Optimization
Luyu Jiang, Dantong Ouyang, Qi Zhang +1
Local search is an effective method for solving large-scale combinatorial optimization problems, and it has made remarkable progress in recent years through several subtle mechanis…
Disentangled Dynamic Graph Deep Generation
Wenbin Zhang, Liming Zhang, Dieter Pfoser +1
Deep generative models for graphs have exhibited promising performance in ever-increasing domains such as design of molecules (i.e, graph of atoms) and structure prediction of prot…
Factorized Deep Generative Models for Trajectory Generation with Spatiotemporal-Validity Constraints
Liming Zhang, Liang Zhao, Dieter Pfoser
Trajectory data generation is an important domain that characterizes the generative process of mobility data. Traditional methods heavily rely on predefined heuristics and distribu…
TG-GAN: Continuous-time Temporal Graph Generation with Deep Generative Models
Liming Zhang, Liang Zhao, Shan Qin +1
The recent deep generative models for static graphs that are now being actively developed have achieved significant success in areas such as molecule design. However, many real-wor…
Station-to-User Transfer Learning: Towards Explainable User Clustering Through Latent Trip Signatures Using Tidal-Regularized Non-Negative Matrix Factorization
Liming Zhang, Andreas Züfle, Dieter Pfoser
Urban areas provide us with a treasure trove of available data capturing almost every aspect of a population's life. This work focuses on mobility data and how it will help improve…
Conditional-UNet: A Condition-aware Deep Model for Coherent Human Activity Recognition From Wearables
Liming Zhang
Recognizing human activities from multi-channel time series data collected from wearable sensors is ever more practical. However, in real-world conditions, coherent activities and…