Chongliang Wu

According to our database1, Chongliang Wu authored at least 12 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
The USTC-Nercslip Systems for the ICMC-ASR Challenge.
Proceedings of the IEEE International Conference on Acoustics, 2024

2018
The USTC-NEL Speech Translation system at IWSLT 2018.
Proceedings of the 15th International Conference on Spoken Language Translation, 2018

2016
Capturing global spatial patterns for distinguishing posed and spontaneous expressions.
Comput. Vis. Image Underst., 2016

Posed and Spontaneous Expression Recognition Through Restricted Boltzmann Machine.
Proceedings of the MultiMedia Modeling - 22nd International Conference, 2016

Facial Expression Recognition with Deep two-view Support Vector Machine.
Proceedings of the 2016 ACM Conference on Multimedia Conference, 2016

Emotion Recognition from EEG Signals Enhanced by User's Profile.
Proceedings of the 2016 ACM on International Conference on Multimedia Retrieval, 2016

Implicit hybrid video emotion tagging by integrating video content and users' multiple physiological responses.
Proceedings of the 23rd International Conference on Pattern Recognition, 2016

2015
Posed and spontaneous expression recognition through modeling their spatial patterns.
Mach. Vis. Appl., 2015

Multi-instance Hidden Markov Model for facial expression recognition.
Proceedings of the 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, 2015

Posed and spontaneous facial expression differentiation using deep Boltzmann machines.
Proceedings of the 2015 International Conference on Affective Computing and Intelligent Interaction, 2015

2014
Capture expression-dependent AU relations for expression recognition.
Proceedings of the 2013 IEEE International Conference on Multimedia and Expo Workshops, 2014

Facial Action Unit recognition by relation modeling from both qualitative knowledge and quantitative data.
Proceedings of the 2013 IEEE International Conference on Multimedia and Expo Workshops, 2014


  Loading...