Dr. Hyung Jin Chang

Associate Professor @ University of Birmingham


I am a Associate Professor of the School of Computer Science at the University of Birmingham and a Turing Fellow of the Alan Turing Institute. My research interests are focused on human-centred visual learning, especially in application to human-robot interaction. Computer vision and machine learning including deep learning are my expertise research area.

I am always looking for fully motivated & talented PhD students!

Contact Me

  • Office: Room 107, School of Computer Science
  • E-mail: H.J.Chang@bham.ac.uk
  • Phone: +44(0)121 414 7264


Selected Publications

  1. CVPR’22
    Collaborative Learning for Hand and Object Reconstruction with Attention-guided Graph Convolution
    Tse, Tze Ho Elden, Kim, Kwang In, Leonardis, Ales, and Chang, Hyung Jin
    In IEEE Computer Vision and Pattern Recognition (CVPR) 2022
  2. ICRA’22
    TP-AE: Temporally Primed 6D Object Pose Tracking with Auto-Encoders
    Zheng, Linfang, Leonardis, Ales, Tse, Tze Ho Elden, Horanyi, Nora, Chen, Hua, Zhang, Wei, and Chang, Hyung Jin
    In 2022 IEEE International Conference on Robotics and Automation (ICRA) 2022
  3. PR’22
    Repurposing Existing Deep Networks for Caption and Aesthetic-Guided Image Cropping
    Horanyi, Nora, Xia, Kedi, Yi, Kwang Moo, Bojja, Abhishake Kumar, Leonardis, Aleš, and Chang, Hyung Jin
    Elsevier Pattern Recognition 2022
  4. WACV’22
    Novel-View Synthesis of Human Tourist Photos
    Freer, Jonathan, Yi, Kwang Moo, Jiang, Wei, Choi, Jongwon, and Chang, Hyung Jin
    In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision 2022
  5. CVPR’21
    Vab-al: Incorporating class imbalance and difficulty with variational bayes for active learning
    Choi, Jongwon, Yi, Kwang Moo, Kim, Jihoon, Choo, Jinho, Kim, Byoungjip, Chang, Jinyeop, Gwon, Youngjune, and Chang, Hyung Jin
    In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2021
  6. TPAMI’18
    Highly articulated kinematic structure estimation combining motion and skeleton information
    Chang, Hyung Jin, and Demiris, Yiannis
    IEEE Transactions on Pattern Analysis and Machine Intelligence 2018
  7. TPAMI’17
    Learning kinematic structure correspondences using multi-order similarities
    Chang, Hyung Jin, Fischer, Tobias, Petit, Maxime, Zambelli, Martina, and Demiris, Yiannis
    IEEE transactions on pattern analysis and machine intelligence 2017
  8. TPAMI’16
    Latent regression forest: structured estimation of 3d hand poses
    Tang, Danhang, Chang, Hyung Jin, Tejani, Alykhan, and Kim, Tae-Kyun
    IEEE Transactions on Pattern Analysis and Machine Intelligence 2016