professor at Universiti Malaya

My research interests include computer vision and machine learning, where I lead a young and energetic research team that has published more than 100 papers in related top peer-review conferences and journals (e.g. CVPR, NeurIPS, TPAMI, TIP etc). I was the founding Chair for IEEE Computational Intelligence Society, Malaysia chapter.

Also currently, I serve as the Associate Editor of Pattern Recognition (Elsevier), and have co-organized several conferences/workshops/tutorials/challenges related to computer vision/machine learning. I was the recipient of Top Research Scientists Malaysia (TRSM) in 2022, Young Scientists Network Academy of Sciences Malaysia (YSN-ASM) in 2015 and Hitachi Research Fellowship in 2013. Besides that, I am also a senior member (IEEE), Professional Engineer (BEM) and Chartered Engineer (IET).

During 2020-2022, I was seconded to the Ministry of Science, Technology and Innovation (MOSTI) as the Undersecretary for Division of Data Strategic and Foresight.

      02/2024: One(1) paper to appear in CVPR-2024. Please see Project Page.
      08/2023: One(1) paper (oral) to appear in BMVC-2023. Please see Project Page.

Latest Works

InteractDiffusion: Interaction-Control for Text-to-Image Diffusion Model Star

J.T. Hoe, X. Jiang, C.S. Chan, Y-P. Tan and W. Hu
CVPR 2024 (acceptance rate: 2719/11532 ~ 23.6%)


Existing methods lack ability to control the interactions between objects in the generated content. This paper proposes a pluggable interaction control model, called InteractDiffusion that extends existing pre-trained T2I diffusion models to enable them being better conditioned on interactions.

pdf poster code video demo

SFAMNet: A scene flow attention-based micro-expression network Star

G-B. Liong, S-T. Liong, C.S. Chan and J. See
Neurocomputing (2024)


This paper proposes the first Scene Flow Attention-based Micro-expression Network, namely SFAMNet. Extensive experiments performed on three tasks: (i) ME spotting; (ii) ME recognition; and (iii) ME analysis on the multi-modal CAS(ME)^3 dataset indicate that depth is vital in capturing the ME information.

pdf code

Unsupervised Hashing with Similarity Distribution Calibration Star

K.W. Ng, X. Zhu, J.T. Hoe, C.S. Chan, T. Zhang, Y-Z. Song and T. Xiang
BMVC 2023 (oral, acceptance rate: ~ 7.5%)


This paper proposes Similarity Distribution Calibration (SDC) method to align the hash code similarity distribution towards a calibration distribution (e.g., beta distribution) with sufficient spread across the entire similarity range, in order to alleviate the similarity collapse problem.

pdf slide code

Cycle-object consistency for image-to-image domain adaptation Star

C-T. Lin, J-L. Kew, C.S. Chan, S-H. Lai and C. Zach
Pattern Recognition (2023)


This work is focused on image2image domain adaptation (see pic beside) where we introduced an instance-aware GAN framework, AugGAN-Det, to jointly train a generator with an object detector (for image object style) and a discriminator (for global style).