Area of research
Computer Vision and Pattern Recognition · Artificial Intelligence
Research interest
Research interests include Domain Adaptation and Few-Shot Learning, Human Pose and Action Recognition, Video Surveillance and Tracking Methods, and Advanced Neural Network Applications.
Coarse-to-Fine Latent Diffusion for Pose-Guided Person Image Synthesis
Pair Shuffle Consistency for Semi-supervised Medical Image Segmentation
DilateFormer: Multi-Scale Dilated Transformer for Visual Recognition
Adversarial Feature Augmentation for Cross-domain Few-Shot Classification
Hierarchical feature disentangling network for universal domain adaptation
Multi-level Attentive Adversarial Learning with Temporal Dilation for Unsupervised Video Domain Adaptation
Removing the Background by Adding the Background: Towards Background Robust Self-supervised Video Representation Learning
Weakly Supervised Liver Tumor Segmentation Using Couinaud Segment Annotation
Explainable Uncertainty-Aware Convolutional Recurrent Neural Network for Irregular Medical Time Series
Adversarial open set domain adaptation via progressive selection of transferable target samples
Multi-Scale Adversarial Cross-Domain Detection with Robust Discriminative Learning
Dynamic Graph Co-Matching for Unsupervised Video-Based Person Re-Identification
Semi-supervised Region Metric Learning for Person Re-identification
Joint Sparse Representation and Robust Feature-Level Fusion for Multi-Cue Visual Tracking