81 citations · 100 across the 10 of their papers we have counts for
10 papers
Learning Geometric Invariance for Gait Recognition
Zengbin Wang, Junjie Li, Saihui Hou +6
The goal of gait recognition is to extract identity-invariant features of an individual under various gait conditions, e.g., cross-view and cross-clothing. Most gait models strive…
QAGait: Revisit Gait Recognition from a Quality Perspective
Zengbin Wang, Saihui Hou, Man Zhang +5
Gait recognition is a promising biometric method that aims to identify pedestrians from their unique walking patterns. Silhouette modality, renowned for its easy acquisition, simpl…
FastPoseGait: A Toolbox and Benchmark for Efficient Pose-based Gait Recognition
Shibei Meng, Yang Fu, Saihui Hou +3
We present FastPoseGait, an open-source toolbox for pose-based gait recognition based on PyTorch. Our toolbox supports a set of cutting-edge pose-based gait recognition algorithms…
Free Lunch for Gait Recognition: A Novel Relation Descriptor
Jilong Wang, Saihui Hou, Yan Huang +5
Gait recognition is to seek correct matches for query individuals by their unique walking patterns. However, current methods focus solely on extracting individual-specific features…
Unsupervised Gait Recognition with Selective Fusion
Xuqian Ren, Shaopeng Yang, Saihui Hou +3
Previous gait recognition methods primarily trained on labeled datasets, which require painful labeling effort. However, using a pre-trained model on a new dataset without fine-tun…
Deep Learning-based Occluded Person Re-identification: A Survey
Yunjie Peng, Saihui Hou, Chunshui Cao +3
Occluded person re-identification (Re-ID) aims at addressing the occlusion problem when retrieving the person of interest across multiple cameras. With the promotion of deep learni…
Progressive Feature Learning for Realistic Cloth-Changing Gait Recognition
Xuqian Ren, Saihui Hou, Chunshui Cao +2
Gait recognition is instrumental in crime prevention and social security, for it can be conducted at a long distance to figure out the identity of persons. However, existing datase…
Data Augmentation For Medical MR Image Using Generative Adversarial Networks
Panjian Huang, Xu Liu, Yongzhen Huang
Computer-assisted diagnosis (CAD) based on deep learning has become a crucial diagnostic technology in the medical industry, effectively improving diagnosis accuracy. However, the…
A novel meta-learning initialization method for physics-informed neural networks
Xu Liu, Xiaoya Zhang, Wei Peng +2
Physics-informed neural networks (PINNs) have been widely used to solve various scientific computing problems. However, large training costs limit PINNs for some real-time applicat…
Feature Super-Resolution Based Facial Expression Recognition for Multi-scale Low-Resolution Faces
Wei Jing, Feng Tian, Jizhong Zhang +3
Facial Expressions Recognition(FER) on low-resolution images is necessary for applications like group expression recognition in crowd scenarios(station, classroom etc.). Classifyin…