Area of research
Computer Vision and Pattern Recognition · Artificial Intelligence
Research interest
Research interests include Computer science, Artificial intelligence, Convolutional neural network, Benchmark (surveying), Embedding, and Deep learning.
DeepDance: Music-to-Dance Motion Choreography With Adversarial Learning
Surface-Electromyography-Based Gesture Recognition by Multi-View Deep Learning
Learning to Detect Human-Object Interactions With Knowledge
Interact as You Intend: Intention-Driven Human-Object Interaction Detection
Explainable Video Action Reasoning via Prior Knowledge and State Transitions
A novel attention-based hybrid CNN-RNN architecture for sEMG-based gesture recognition
Dual-Stream Recurrent Neural Network for Video Captioning
Multi-Modal and Multi-Domain Embedding Learning for Fashion Retrieval and Analysis
Unsupervised Learning of View-invariant Action Representations
arXiv (Cornell University) 2018cited by 44position: middle
A multi-stream convolutional neural network for sEMG-based gesture recognition in muscle-computer interface
Dual-Glance Model for Deciphering Social Relationships
Understanding Fashion Trends from Street Photos via Neighbor-Constrained Embedding Learning
Marker-Less 3D Human Motion Capture with Monocular Image Sequence and Height-Maps
Benchmarking a Multimodal and Multiview and Interactive Dataset for Human Action Recognition
Automatic classification of Human Epithelial type 2 cell Indirect Immunofluorescence images using Cell Pyramid Matching