2014 December - Lamma Island

About

Welcome to the Video, Image, and Sound Analysis Lab (VISAL) at the City University of Hong Kong! The lab is directed by Dr. Antoni Chan in the Department of Computer Science.

Our main research activities include:

  • Computer Vision, Surveillance
  • Machine Learning, Pattern Recognition
  • Computer Audition, Music Information Retrieval
  • Eye Gaze Analysis

For more information about our current research, please visit the projects and publication pages.

Opportunities for graduate students and research assistants - if you are interested in joining the lab, please check this information.

New! A postdoc position is available with my collaborator at HKU — the project is about using machine learning to analyze eye gaze.

Latest News [more]

  • [Jun 28, 2016]

    Congratulations to Sijin for defending his thesis!

  • [Jun 25, 2016]

    Congratulations to Adeel for winning a “Best Research Paper Award 2013/14″ from the Higher Education Commission (HEC) of Pakistan for his TPAMI 2013 paper!

  • [Apr 26, 2016]

    Congratulations to Huy for defending his Thesis!

  • [Mar 18, 2016]

    Congratulations to Zheng for defending his thesis!

Recent Publications [more]

Recent Project Pages [more]

Maximum-Margin Structured Learning with Deep Networks for 3D Human Pose Estimation

We propose a maximum-margin structured learning framework with deep neural network that learns the image-pose score function for human pose estimation.

imgposeembed5
Small Instance Detection using Object Density Maps

We propose a novel object detection framework using object density maps for partially-occluded small instances, such as pedestrians in low resolution surveillance video.

videoImg_0045
Pose Estimation with Deep Convolutional Neural Network

We propose a heterogeneous multi-task learning framework for 2D human pose estimation from monocular images using a deep convolutional neural network that combines pose regression and part detection. We also extend the model to 3D human pose estimation.

deep-pose-conv-r1-for-demo