About Me

  • I am currently a Senior Research Scientist at Visual Intelligence Department of Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR), Singapore.

  • I obtained my Bachelor Degree from Beijing Institute of Technology at 2013 and PhD Degree from Nanyang Technological University (NTU), Singapore at 2019. After graduation, I have been working in I2R, A*STAR as a research scientist.

  • My current reserach interests are in thoery and application in machine learning, deep learning and computer vision.

  • For my detailed working and research experience, please refer to CV for my complete CV.

Recent News

  • One paper entitled “PartCLIP: How does CLIP assist mechanical part image retrieval?” has been accepted in ICMEW2024.

  • My Research Work on Multi-View 3D Object Recognition and Retrieval is shown in A*STAR Research Highlight Page Link

  • My Research Work on Defect Detection and Segmentation is shown in A*STAR Research Highlight Page Link

  • One paper entitled “SCA-PVNet: Self-and-cross attention based aggregation of point cloud and multi-view for 3D object retrieval” has been published in Knowledge-Based Systems.

  • One paper entitled “Keyword-Aware Relative Spatio-Temporal Graph Networks for Video Question Answering” has been published in IEEE Transactions on Multimedia.

  • One US Patent entitled “Method and system for image classification” has been granted with Patent Number: 11836632.

  • Our solution has won the 1st Place in EPIC-Kitchens Dataset Challenges: Unsupervised Domain Adaptation for Action Recognition Track, CVPR2023 Leaderboard Link

  • One paper entitled “DDR-ID: Dual deep reconstruction networks based image decomposition for anomaly detection” has been published in Journal of Ambient Intelligence and Humanized Computing.

  • One paper entitled “Multi-range view aggregation network with vision transformer feature fusion for 3D object retrieval” has been published in IEEE Transactions on Multimedia.

  • One paper entitled “An effective industrial defect classification method under the few-shot setting via two-stream training” has been published in Optics and Lasers in Engineering.

  • One paper entitled “Biomedical image classification based on a feature concatenation and ensemble of deep CNNs” has been published in Journal of Ambient Intelligence and Humanized Computing.

  • Three papers entitled “MLSA-UNet: End-to-End multi-level spatial attention guided UNet for industrial defect segmentation”, “Masked face recognition via self-attention based local consistency regularization” and “Implicit shape biased few-shot learning for 3d object generalization” have been published in ICIP2022.

  • One paper entitled “Multi-view 3D object retrieval leveraging the aggregation of view and instance attentive features” has been published in Knowledge-Based Systems.

  • One paper entitled “On the use of component structural characteristics for voxel segmentation in semicon 3D images” has been published in ICASSP2022.

  • Our solution has won the 1st Place in EPIC-Kitchens Dataset Challenges: Unsupervised Domain Adaptation for Action Recognition Track, CVPR2022 Leaderboard Link

  • One paper entitled “A progressive multi-view learning approach for multi-loss optimization in 3d object recognition” has been published in IEEE Signal Processing Letters.

  • One paper entitled “CAM-guided Multi-Path Decoding U-Net with Triplet Feature Regularization for defect detection and segmentation” has been published in Knowledge-Based Systems.

  • Two papers entitled “CAM-Guided u-net with adversarial regularization for defect segmentation” and “Action Relational Graph for Weakly-Supervised Temporal Action Localization” have been published in ICIP2021.

  • One paper entitled “Few-shot defect segmentation leveraging abundant defect-free training samples through normal background regularization and crop-and-paste operation” has been published in ICME2021(Oral Presentation).

  • One paper entitled “Rethinking of deep models parameters with respect to data distribution” has been published in ICPR2021.

  • One paper entitled “maskedfacenet: A progressive semi-supervised masked face detector” has been published in WACV2021.

  • Two papers entitled “CAM-UNET: class activation MAP guided UNET with feedback refinement for defect segmentation” and “Improving 3d brain tumor segmentation with predict-refine mechanism using saliency and feature maps” have been published in ICIP2020.

  • One paper entitled “RefineU-Net: Improved U-Net with progressive global feedbacks and residual attention guided local refinement for medical image segmentation” has been published in Pattern Recognition Letters.

  • One paper entitled “Discriminative features for incremental learning classifier” has been published in ICIP2019.

  • One paper entitle “A two-stage method for automated detection of ring-like endosomes in fluorescent microscopy images” has been published in Plos One.

  • One paper entitled “Vibration source classification and propagation distance estimation system based on spectrogram and KELM” has been published in Cognitive Computation and Systems.

  • One paper entitled “Meta module generation for fast few-shot incremental learning” has been published in ICCVW2019.

  • One paper entitled “Multicomponent signal decomposition using morphological operations” has been published in DSP2018.

  • One paper entitled “Deep CNNs for microscopic image classification by exploiting transfer learning and feature concatenation” has been published in ISCAS2018.

  • One paper entitled “Biomedical image classification based on a cascade of an SVM with a reject option and subspace analysis” has been published in Computers in biology and medicine.

  • One paper entitled “Twin SVM with a reject option through ROC curve” has been published in Journal of the Franklin Institute.

  • Two papers entitled “Automatic endosomal structure detection and localization in fluorescence microscopic images” and “LLC encoded BoW features and softmax regression for microscopic image classification” have been published in ISCAS2017.

  • One paper entitled “Reaction-diffusion based level set method with local entropy thresholding for melasma image segmentation” has been published in ISCAS2017.

  • One paper entiteld “An SVM based scoring evaluation system for fluorescence microscopic image classification” has been published in DSP2015.