Liu Jun

Home / People / Faculty / Liu Jun
Go back to faculty list

Assistant Professor

Email: 
Telephone: +65 6499 8895
Office #: 1.502.33
Pillar / Cluster: Information Systems Technology and Design
Research Areas:Artificial and Augmented Intelligence, Visual Computing, Data Science

Biography

Jun Liu received the PhD degree from Nanyang Technological University in 2019. His research interests include computer vision and artificial intelligence. His works have been published in premier computer vision journals and conferences, including TPAMI, CVPR, ICCV, and ECCV. He received several best paper awards from the Pattern Recognition and Machine Intelligence Association of Singapore for his works on video analytics and human activity understanding. He received the EEE Best Thesis Award from Nanyang Technological University in 2020.

Open Positions

I am currently looking for motivated PhD students, Research Assistants, and Visiting Students with strong interests in computer vision and machine learning. If interested, kindly contact me via email.

Selected Publications

For a full list of my publications, please see my Google Scholar Page.

  • Tianjiao Li, Jun Liu, Wei Zhang, Lingyu Duan, HARD-Net: Hardness-AwaRe Discrimination Network for 3D Early Activity Prediction, European Conference on Computer Vision (ECCV), 2020.
  • Zhipeng Fan, Jun Liu, Yao Wang, Adaptive Computationally Efficient Network for Monocular 3D Hand Pose Estimation, European Conference on Computer Vision (ECCV), 2020. (Spotlight Paper)
  • Siyuan Yang, Jun Liu, Shijian Lu, Meng Hwa Er, Alex C. Kot, Collaborative Learning of Gesture Recognition and 3D Hand Pose Estimation with Multi-Order Feature Analysis, European Conference on Computer Vision (ECCV), 2020. (Spotlight Paper)
  • Yujun Cai, Lin Huang, Yiwei Wang, Tat-Jen Cham, Jianfei Cai, Junsong Yuan, Jun Liu, et al., Learning Progressive Joint Propagation for Human Motion Prediction, European Conference on Computer Vision (ECCV), 2020.
  • Yan Bai, Yihang Lou, Yongxing Dai, Jun Liu, Ziqian Chen, Lingyu Duan, Disentangled Feature Learning Network for Vehicle Re-Identification, International Joint Conference on Artificial Intelligence (IJCAI), 2020.
  • Jun Liu, Henghui Ding, Amir Shahroudy, Ling-Yu Duan, Xudong Jiang, Gang Wang, Alex C. Kot, Feature Boosting Network for 3D Pose Estimation, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020. (IF=17.9)
  • Jun Liu, Amir Shahroudy, Gang Wang, Ling-Yu Duan, Alex C. Kot, Skeleton-Based Online Action Prediction Using Scale Selection Network, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020. (IF=17.9, PREMIA Best Student Paper Silver Award)
  • Jun Liu, Amir Shahroudy, Mauricio Perez, Gang Wang, Ling-Yu Duan, Alex C. Kot, NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020. (IF=17.9)
  • Jun Wan, Zhihui Lai, Jun Liu, Jie Zhou, Can Gao, Robust Face Alignment by Multi-order High-precision Hourglass Networks, IEEE Transactions on Image Processing (TIP), 2020.
  • Xiaohong Wang, Xudong Jiang, Henghui Ding, Jun Liu, Bi-directional Dermoscopic Feature Learning and Multi-scale Consistent Decision Fusion for Skin Lesion Segmentation, IEEE Transactions on Image Processing (TIP), 2020.
  • Yihang Lou, Yan Bai, Jun Liu, Shiqi Wang, Ling-Yu Duan, VERI-Wild: A Large Dataset and a New Method for Vehicle Re-Identification in the Wild, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
  • Yujun Cai, Liuhao Ge, Jun Liu, Jianfei Cai, Tat-Jen Cham, Junsong Yuan, and Nadia Magnenat Thalmann, Exploiting Spatial-temporal Relationships for 3D Pose Estimation via Graph Convolutional Networks, IEEE International Conference on Computer Vision (ICCV), 2019.
  • Yihang Lou, Yan Bai, Jun Liu, Shiqi Wang, Ling-Yu Duan, Embedding Adversarial Learning for Vehicle Re-Identification, IEEE Transactions on Image Processing (TIP), 2019.
  • Jun Liu, Amir Shahroudy, Gang Wang, Ling-Yu Duan, Alex C. Kot, SSNet: Scale selection network for online 3D action prediction, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. (Spotlight Paper)
  • Jun Liu, Amir Shahroudy, Dong Xu, Alex C. Kot, Gang Wang, Skeleton-Based Action Recognition Using Spatio-Temporal LSTM Network with Trust Gates, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2018. (IF=17.9)
  • Jun Liu, Gang Wang, Ling-Yu Duan, Kamila Abdiyeva, Alex C. Kot, Skeleton-Based Human Action Recognition with Global Context-Aware Attention LSTM Networks, IEEE Transactions on Image Processing (TIP), 2018.
  • Jun Liu, Gang Wang, Ping Hu, Ling-Yu Duan, Alex C. Kot, Global context-aware attention LSTM networks for 3D action recognition, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
  • Ping Hu, Bing Shuai, Jun Liu, Gang Wang, Deep level sets for salient object detection, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
  • Jun Liu, Amir Shahroudy, Dong Xu, Gang Wang, Spatio-temporal LSTM with trust gates for 3D human action recognition, European Conference on Computer Vision (ECCV), 2016. (PREMIA Best Student Paper Silver Award)
  • Amir Shahroudy, Jun Liu, Tian-Tsong Ng, Gang Wang, NTU RGB+D: A large scale dataset for 3D human activity analysis, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.

Research Interests

Computer Vision, Machine Learning, and Artificial Intelligence

Go back to faculty list