Hello! Iโ€™m Yunkang Cao (ๆ›นไบ‘ๅบท), a Ph.D. candidate at Huazhong University of Science and Technology (HUST), where I am honored to be working under the guidance of Prof. Weiming Shen. I am also grateful for the opportunity to visit Politecnico di Milano (Polimi) for one year, working under the supervision of Prof. Giacomo Boracchi.

My academic research primarily focuses on Deep Learning and Computer Vision, with a particular emphasis on Multi-modal Anomaly Detection. Recently, my work has concentrated on leveraging foundational models such as vision-language models for anomaly detection tasks, as well as exploring Zero/Few-shot Anomaly Detection. Beyond visual anomaly detection, my long-term goal is to enhance intelligent visual systems with reasoning and planning capabilities to address and recover from open-world anomalies. This approach is designed to improve the robustness and safety of applications in fields like intelligent manufacturing and autonomous driving. If you find my research interesting, I would love to connect! Feel free to reach out if you have any questions or would like to discuss my work. ๐Ÿ˜Š

Additionally, I am currently exploring postdoctoral opportunities. If you know of any openings or are interested in potential collaborations, please donโ€™t hesitate to email me!

๐Ÿ”ฅ News

๐Ÿ“ Publications

Peer-Reviewed Publications 
Manuscripts under Review 

# co-first author | * corresponding author

Peer-Reviewed Publications

  1. Exploring Intrinsic Normal Prototypes within a Single Image for Universal Anomaly Detection [Paper] [Code]
    Wei Luo#, Yunkang Cao#, Haiming Yao#, Xiaotian Zhang, Jianan Lou, Yuqi Cheng, Weiming Shen, Wenyong Yu*
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2025.
  2. Anomaly Anything: Promptable Unseen Visual Anomaly Generation [Paper] [Code]
    Han Sun, Yunkang Cao, Hao Dong, Olga Fink*
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2025.
  3. Customizing Visual-Language Foundation Models for Multi-Modal Anomaly Detection and Reasoning [Paper] [Code]
    Xiahao Xu#, Yunkang Cao#, Huaxin Zhang, Nong Sang, Xiaonan Huang, Weiming Shen*
  4. Personalizing Vision-Language Models with Hybrid Prompts for Zero-Shot Anomaly Detection [Paper] [Code]
    Yunkang Cao, Xiaohao Xu, Yuqi Cheng, Chen Sun, Zongwei Du, Liang Gao, Weiming Shen*
    IEEE Transactions on Cybernetics (IEEE TCYB). 2025.
  5. VarAD: Lightweight High-Resolution Image Anomaly Detection via Visual Autoregressive Modeling
    Yunkang Cao, Haiming Yao, Wei Luo, Weiming Shen*
    IEEE Transactions on Industrial Informatics (IEEE TII). 2025.
  6. AdaCLIP: Adapting CLIP with Hybrid Learnable Prompts for Zero-Shot Anomaly Detection [Paper] [Code]
    Yunkang Cao, Jiangning Zhang, Luca Frittoli, Yuqi Cheng, Weiming Shen*, Giacomo Boracchi
    European Conference on Computer Vision (ECCV). 2024.
  7. Complementary pseudo multimodal feature for point cloud anomaly detection [Paper] [Code]
    Yunkang Cao, Xiaohao Xu, Weiming Shen*
    Pattern Recognition (PR). 2024.
  8. BiaS: Incorporating Biased Knowledge to Boost Unsupervised Image Anomaly Localization [Paper]
    Yunkang Cao, Xiaohao Xu, Chen Sun, Liang Gao, Weiming Shen*
    IEEE Transactions on Systems, Man, and Cybernetics: Systems (IEEE TSMC). 2024.
  9. Collaborative discrepancy optimization for reliable image anomaly localization [Paper] [Code]
    Yunkang Cao, Xiaohao Xu, Zhaoge Liu, Weiming Shen*
    IEEE Transactions on Industrial Informatics (IEEE TII). 2023.
  10. High-Resolution Image Anomaly Detection via Spatiotemporal Consistency Incorporated Knowledge Distillation [Paper]
    Yunkang Cao, Yiheng Zhang, Weiming Shen*
    IEEE International Conference on Automation Science and Engineering (IEEE CASE). 2023.
  11. Informative knowledge distillation for image anomaly segmentation [Paper] [Code]
    Yunkang Cao, Qian Wan, Weiming Shen*, Liang Gao
    Knowledge-Based Systems (KBS). 2022.
  12. Boosting Global-Local Feature Matching via Anomaly Synthesis for Multi-Class Point Cloud Anomaly Detection
    Yuqi Cheng, Yunkang Cao, Dongfang Wang, Weiming Shen*, Wenlong Li
    IEEE Transactions on Automation Science and Engineering (IEEE TASE). 2025.
  13. Prototypical Learning Guided Context-Aware Segmentation Network for Few-Shot Anomaly Detection [Paper] [Code]
    Yuxin Jiang, Yunkang Cao, Weiming Shen*
    IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS). 2024.
  14. LogiCode: an LLM-Driven Framework for Logical Anomaly Detection [Paper] [Code]
    Yiheng Zhang, Yunkang Cao, Xiaohao Xu, Weiming Shen*
    IEEE Transactions on Automation Science and Engineering (IEEE TASE). 2024.
  15. Prior Normality Prompt Transformer for Multi-class Industrial Image Anomaly Detection [Paper]
    Haiming Yao, Yunkang Cao, Wei Luo, Weihang Zhang, Wenyong Yu*, Weiming Shen
    IEEE Transactions on Industrial Informatics (IEEE TII). 2024.
  16. Deep Feature Contrasting for Industrial Image Anomaly Segmentatio [Paper]
    Qian Wan, Yunkang Cao, Liang Gao, Xinyu Li*, Yiping Gao
    IEEE Transactions on Instrumentation and Measurement (IEEE TIM). 2024.
  17. Dual-path Frequency Discriminators for Few-shot Anomaly Detection
    Yuhu Bai#, Jiangning Zhang#, Zhaofeng Chen, Yuhang Dong, Yunkang Cao, Guanzhong Tian*
    Knowledge-Based Systems (KBS). 2024.
  18. Generative Denoise Distillation: Simple Stochastic Noises Induce Efficient Knowledge Transfer for Dense Prediction
    Zhaoge Liu, Xiaohao Xu, Yunkang Cao, Weiming Shen*
    Knowledge-Based Systems (KBS). 2024.
  19. RAD: A Comprehensive Dataset for Benchmarking the Robustness of Image Anomaly Detection [Paper] [Code]
    Yuqi Cheng, Yunkang Cao, Rui Chen, Weiming Shen*
    IEEE International Conference on Automation Science and Engineering (IEEE CASE). 2024.
  20. Attention Fusion Reverse Distillation for Multi-Lighting Image Anomaly Detection [Paper]
    Yiheng Zhang, Yunkang Cao, Tianhang Zhang, Weiming Shen*
    IEEE International Conference on Automation Science and Engineering (IEEE CASE). 2024.
  21. A masked reverse knowledge distillation method incorporating global and local information for image anomaly detection [Paper] [Code]
    Yuxin Jiang, Yunkang Cao, Weiming Shen*
    Knowledge-Based Systems (KBS). 2023.
  22. Position encoding enhanced feature mapping for image anomaly detection [Paper] [Code]
    Qian Wan, Yunkang Cao, Liang Gao, Weiming Shen, Xinyu Li*
    IEEE International Conference on Automation Science and Engineering (IEEE CASE). 2022.

Manuscripts under Review

  1. A Generalized Medical Anomaly Detection Suite: Detecting Anomalies in Multi-Source and Multi-Modality Images.
    Yunkang Cao#, Haiming Yao#, Yu Cai, Hao Chen, Weiming Shen*
    IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS). (under review)
  2. A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect [Paper]
    Yunkang Cao, Xiaohao Xu, Jiangning Zhang, Yuqi Cheng, Xiaonan Huang, Guansong Pang, Weiming Shen* (under review)
  3. Towards Zero-shot Point Cloud Anomaly Detection: A Multi-View Projection Framework [Paper] [Code]
    Yuqi Cheng#, Yunkang Cao#, Guoyang Xie, Zhichao Lu, Weiming Shen*
    IEEE Transactions on Systems, Man, and Cybernetics: Systems (IEEE TSMC) . (major revision)
  4. VTFusion: A Vision-Text Multimodal Fusion Network for Few-Shot Anomaly Detection
    Yuxin Jiang, Yunkang Cao, Yuqi Cheng, Yiheng Zhang, Weiming Shen*
    IEEE Transactions on Cybernetics (IEEE TCYB). (major revision)
  5. Global-Regularized Neighborhood Regression for Efficient Zero-Shot Texture Anomaly Detection [Paper] [Code]
    Haiming Yao, Wei Luo, Yunkang Cao, Yiheng Zhang, Wenyong Yu*, Weiming Shen
    IEEE Transactions on Systems, Man, and Cybernetics: Systems (IEEE TSMC). (major revision)
  6. URA-Net: Uncertainty-Integrated Anomaly Perception and Restoration Attention Network for Unsupervised Anomaly Detection
    Wei Luo, Peng Xing, Yunkang Cao, Haiming Yao, Weiming Shen, Zechao Li* (under review)

๐Ÿ’ป Projects

Mobile E-Ink Screen Surface Defect Detection Equipment Jun. 2023 - Present
  • constructed a high-resolution defect inspection prototype for mobile e-ink screens.
  • collected a comprehensive dataset of high-resolution images for mobile e-ink screen inspection.
  • translated image anomaly detection into token prediction, and introduced state space models to predict the future tokens based on previous tokens.
  • achieved high detection efficiency with great global information capture capacity for high-resolution images.
Complex Surface Part Inspection Equipment Jun. 2020 - Jun. 2024
  • constructed a multi-view and multi-illumination defect inspection prototype equipment for curved surface parts.
  • collected an automotive part inspection dataset featuring multi-illumination images.
  • proposed a multi-illumination visual anomaly detection task and extended reverse knowledge distillation for this task.
  • improved 6.5% detection AUROC with minimal additional overhead in comparison to anomaly detection under single illumination.

๐Ÿฅ‡ Selected Awards

  • National Scholarship (the highest scholarship for Ph.D.), 2024.11
  • Provincial Second Prize, China International College Studentsโ€™ Innovation Competition, 2024.08
  • 2nd place in CVPR VAND Zero-shot Anomaly Detection Challenge
  • First-class Scholarship for Postgraduates, HUST, 2020.09, 2021.09, 2022.09
  • Student Award for Research and Innovation, HUST, 2022.05
  • Mathematical Modeling Stars Nomination (TOP 2) in the 18th China Post-graduate Mathematical Contest, 2022.05
  • Merit Postgraduate student, HUST, 2021.09
  • Excellent Graduates, HUST, 2019.06
  • National Scholarship (the highest scholarship for B.E), 2017.09, 2019.09
  • Second Class Prize, Undergraduate Electronics Design Contest, Provincial, 2018.09
  • Third Class Prize, Undergraduate Intelligent Robotics Contest, National, 2018.05

๐ŸŽ“๐Ÿ“š Academic Service

๐Ÿ’ฌ Invited Talks

  • 2024.07, EPFL, โ€œApplication-Oriented Industrial Visual Anomaly Detectionโ€ [Slides].
  • 2023.11, National University of Defense Technology, โ€œOverview of Image Anomaly Detectionโ€”Review, Applications, and Future Prospectsโ€ [Slides].

๐Ÿ“– Educations

  • 2023.10 - 2024.10, Politecnico di Milano

    Department of Electronics, Information and Bioengineering
    Visiting Ph.D. in Computer Science ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย  Advisor: Giacomo Boracchi

  • 2020.09 - present, Huazhong University of Science and Technology

    State Key Laboratory of Digital Manufacturing Equipment and Technology
    Ph.D. Candidate in Mechanical Engineering ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย  Advisor: Weiming Shen

  • 2016.09 - 2020.06, Huazhong University of Science and Technology

    B.S. in Mechanical Design, Manufacture & Automation ย ย ย