Selected Publications
Chen, W., and Zhou, Y.* (2025) Make Domain Shift a Catastrophic Forgetting Alleviator in Class-Incremental Learning. In Proceedings of the AAAI Conference on Artificial Intelligence. [CCF-A类]
Huang, K., Zhou, T., Fu., H., Zhang, Y., Zhou, Y., Gong, C., & Liang, D. (2025) Learnable Prompting SAM-induced Knowledge Distillation for Semi-supervised Medical Image Segmentation. IEEE Transactions on Medical Imaging, DOI: 10.1109/TMI.2025.3530097. [JCR-Q1]
Lu, Z., Zhang, Y., Zhou, Y., Wu, Y., & Zhou, T. (2024) Domain-Interactive Contrastive Learning and Prototype-Guided Self-Training for Cross-Domain Polyp Segmentation. IEEE Transactions on Medical Imaging, DOI: 10.1109/TMI.2024.3443262. [JCR-Q1]
Wu, R., Zhang, C., Zhang, J., Zhou, Y.*, Zhou, T., & Fu, H. (2024) MM-Retinal: Knowledge-Enhanced Foundational Pretraining with Fundus Image-Text Expertise. In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). Cham: Springer Nature Switzerland. [CCF-B类]
Xie, Y., Zhou, T., Zhou, Y.*, & Chen, G. (2024) SimTxtSeg: Weakly-Supervised Medical Image Segmentation with Simple Text Cues. In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). Cham: Springer Nature Switzerland. [CCF-B类]
Zhao, Y., Zhou, Y., Zhang, Y., Wu, Y., & Zhou, T. (2024) TextPolyp: Point-supervised Polyp Segmentation with Text Cues. In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). Cham: Springer Nature Switzerland. [CCF-B类]
Zhou, T., Zhou, Y., Li, G., Chen, G., & Shen, J. (2024) Uncertainty-aware Hierarchical Aggregation Network for Medical Image Segmentation. IEEE Transactions on Circuits and Systems for Video Technology. DOI:10.1109/TCSVT.2024.3370685. [JCR-Q1]
Luo, S., Chen, W., Wu, R., Geng, S., Zhou, Y.*, et al. (2024) Delving into Multi-modal Multi-task Foundation Models for Road Scene Understanding: From Learning Paradigm Perspectives. IEEE Transactions on Intelligent Vehicles. DOI: 10.1109/TIV.2024.3406372. [JCR-Q1]
Gu, Y., Zhou, T., Zhang, Y., Zhou, Y., He, K., Gong, C., and Fu, H. (2024). Dual-scale Enhanced and Cross-generative Consistency Learning for Semi-supervised Medical Image Segmentation. Pattern Recognition, DOI: 10.1016/j.patcog.2024.110962. [CCF-B类]
Zhou, T., Zhang, Y., Chen, G., Zhou, Y., Wu, Y., and Fan, D. (2024). Edge-aware feature aggregation network for polyp segmentation. Machine Intelligence Research. http://doi.org/10.1007/s11633-023-1479-8. [JCR-Q1]
Lai, Y., Zhou, Y.*, Liu, X., & Zhou, T. (2024). Memory-Assisted Sub-Prototype Mining for Universal Domain Adaptation. In Proceedings of the International Conference on Learning Representations (ICLR). [清华-A类]
Huang, L., Qin, J., Zhou, Y., Zhu, F., Liu, L., & Shao, L. (2023). Normalization techniques in training dnns: Methodology, analysis and application. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(8), 10173–10196. [CCF-A类]
Liu, X., Zhou, Y.*, Zhou T., & Qin J. (2023). Self-Paced Learning for Open-Set Domain Adaptation[J]. Journal of Computer Research and Development (计算机研究与发展), 60(8): 1711-1726. doi: 10.7544/issn1000-1239.202330210. [CCF-A类, Outstanding Paper Award]
Li, Y., Zhou, T., He, K., Zhou, Y., & Shen, D. (2023). Multi-scale Transformer Network with Edge-aware Pre-training for Cross-Modality MR Image Synthesis. IEEE Transactions on Medical Imaging, 42(11), 3395-3407. [JCR-Q1]
Zhou, T., Zhou, Y., He, K., Gong, C., Yang, J., Fu, H., & Shen, D. (2023). Cross-level Feature Aggregation Network for Polyp Segmentation. Pattern Recognition, 140, 109555. [CCF-B类]
Yang, H., Zhou, T., Zhou, Y., Zhang, Y., & Fu, H. (2023). Flexible Fusion Network for Multi-modal Brain Tumor Segmentation. IEEE Journal of Biomedical and Health Informatics, 27(7), 3349-3359. [JCR-Q1]
Zhou, T., Fan, D., Chen G., Zhou, Y., & Fu, H. (2023). Specificity-preserving RGB-D saliency detection. Computer Visual Media Journal, 9(2), 297-317. [JCR-Q1, Honorable Mention Award]
Zhou, T., Zhou, Y., Gong, C., Yang, J., & Zhang, Y. (2022). Feature aggregation and propagation network for camouflaged object detection. IEEE Transactions on Image Processing, 31, 7036-7047. [CCF-A类]
Zhou, H., Huang, Y., Li, Y., Zhou, Y.*, & Zheng, Y. (2022). Blind Super-Resolution of 3D MRI via Unsupervised Domain Transformation. IEEE Journal of Biomedical and Health Informatics, 27(3), 1409-1418. [JCR-Q1]
Zhou, Y., Bai, S., Zhou, T., Zhang, Y., & Fu, H. (2022). Delving into Local Features for Open-Set Domain Adaptation in Fundus Image Analysis. In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) (pp. 682-692). Cham: Springer Nature Switzerland. [CCF-B类]
Huang, L., Zhou, Y., Wang, T., Luo, J., & Liu, X. (2022). Delving into the estimation shift of batch normalization in a network. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 763-772). [CCF-A类]
Zhou, Y., Huang, L., Zhou, T., & Sun, H. (2022). Combating medical noisy labels by disentangled distribution learning and consistency regularization. Future Generation Computer Systems, 141, 567-576. [JCR-Q1]
Zhou, Y., Wang, B., He, X., Cui, S., & Shao, L. (2022). DR-GAN: conditional generative adversarial network for fine-grained lesion synthesis on diabetic retinopathy images. IEEE Journal of Biomedical and Health Informatics, 26(1), 56-66. [JCR-Q1]
Zhou, Y., Huang, L., Zhou, T., & Shao, L. (2021). CCT-Net: category-invariant cross-domain transfer for medical single-to-multiple disease diagnosis. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) (pp. 8260-8270). [CCF-A类]
Zhou, Y., Huang, L., Zhou, T., Fu, H., & Shao, L. (2021). Visual-textual attentive semantic consistency for medical report generation. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) (pp. 3985-3994). [CCF-A类]
Zhou, T., Fu, H., Chen, G., Zhou, Y., Fan, D. P., & Shao, L. (2021). Specificity-preserving RGB-D saliency detection. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) (pp. 4681-4691). [CCF-A类]
Zhou, Y., Zhou, T., Zhou, T., Fu, H., Liu, J., & Shao, L. (2021). Contrast-attentive thoracic disease recognition with dual-weighting graph reasoning. IEEE Transactions on Medical Imaging, 40(4), 1196-1206. [CCF-B类]
Huang, L., Zhou, Y., Liu, L., Zhu, F., & Shao, L. (2021). Group whitening: Balancing learning efficiency and representational capacity. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 9512-9521). [CCF-A类]
Zhou, Y., Huang, L., Zhou, T., & Shao, L. (2021). Many-to-one distribution learning and k-nearest neighbor smoothing for thoracic disease identification. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, No. 1, pp. 768-776). [CCF-A类]
Li, X., Zhou, T., Li, J., Zhou, Y., & Zhang, Z. (2021). Group-wise semantic mining for weakly supervised semantic segmentation. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, No. 3, pp. 1984-1992). [CCF-A类]
Zhou, Y., Wang, B., Huang, L., Cui, S., & Shao, L. (2020). A benchmark for studying diabetic retinopathy: segmentation, grading, and transferability. IEEE Transactions on Medical Imaging, 40(3), 818-828. [CCF-B类]
Fan, D. P., Zhou, T., Ji, G. P., Zhou, Y., Chen, G., Fu, H., ... & Shao, L. (2020). Inf-net: Automatic covid-19 lung infection segmentation from ct images. IEEE Transactions on Medical Imaging, 39(8), 2626-2637. [CCF-B类]
Huang, L., Zhao, L., Zhou, Y., Zhu, F., Liu, L., & Shao, L. (2020). An investigation into the stochasticity of batch whitening. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 6439-6448). [CCF-A类]
Zhou, T., Wang, S., Zhou, Y., Yao, Y., Li, J., & Shao, L. (2020). Motion-attentive transition for zero-shot video object segmentation. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 34, No. 07, pp. 13066-13073). [CCF-A类]
Zhou, Y., He, X., Cui, S., Zhu, F., Liu, L., & Shao, L. (2019). High-resolution diabetic retinopathy image synthesis manipulated by grading and lesions. In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) (pp. 505-513). Cham: Springer International Publishing. [CCF-B类]
He, X., Zhou, Y., Wang, B., Cui, S., & Shao, L. (2019). Dme-net: Diabetic macular edema grading by auxiliary task learning. In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) (pp. 788-796). Cham: Springer International Publishing. [CCF-B类]
Zhou, Y., He, X., Huang, L., Liu, L., Zhu, F., Cui, S., & Shao, L. (2019). Collaborative learning of semi-supervised segmentation and classification for medical images. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 2079-2088). [CCF-A类]
Huang, L., Zhou, Y., Zhu, F., Liu, L., & Shao, L. (2019). Iterative normalization: Beyond standardization towards efficient whitening. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 4874-4883). [CCF-A类]
Wei, Z., Zhang, J., Liu, L., Zhu, F., Shen, F., Zhou, Y., ... & Shao, L. (2019). Building detail-sensitive semantic segmentation networks with polynomial pooling. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 7115-7123). [CCF-A类]
Zhou, Y., & Shao, L. (2018). Viewpoint-aware attentive multi-view inference for vehicle re-identification. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 6489-6498). [CCF-A类]
Zhou, Y., & Shao, L. (2018). Vehicle re-identification by adversarial bi-directional lstm network. In 2018 IEEE Winter Conference on Applications of Computer Vision (WACV) (pp. 653-662). IEEE. [CCF-C类]
Zhou, Y., & Shao, L. (2018). Vehicle re-identification by deep hidden multi-view inference. IEEE Transactions on Image Processing, 27(7), 3275-3287. [CCF-A类]
Liu, L., Zhou, Y., & Shao, L. (2018). Deep action parsing in videos with large-scale synthesized data. IEEE Transactions on Image Processing, 27(6), 2869-2882. [CCF-A类]
Zhou, Y., Liu, L., Shao, L., & Mellor, M. (2017). Fast automatic vehicle annotation for urban traffic surveillance. IEEE Transactions on Intelligent Transportation Systems, 19(6), 1973-1984. [CCF-B类]
Zhou, Y., & Shao, L. (2017). Cross-view GAN based vehicle generation for re-identification. In British Machine Vision Conference (BMVC) (Vol. 1, pp. 1-12). [CCF-C类]
Liu, L., Zhou, Y., & Shao, L. (2017). Dap3d-net: Where, what and how actions occur in videos?. In 2017 IEEE International Conference on Robotics and Automation (ICRA) (pp. 138-145). IEEE. [CCF-B类]
Zhou, Y., Liu, L., Shao, L., & Mellor, M. (2016). DAVE: A unified framework for fast vehicle detection and annotation. In Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part II 14 (pp. 278-293). Springer International Publishing. [CCF-B类]
Academic Services
Reviewer / Program Committee
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
IEEE Transactions on Image Processing
IEEE Transactions on Neural Networks and Learning Systems
Pattern Recognition
IEEE Transactions on Intelligent Transportation Systems
IEEE Transactions on Medical Imaging
Medical Image Analysis
IEEE Journal of Biomedical and Health Informatics
IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
IEEE Conference on Computer Vision (ICCV)
European Conference on Computer Vision (ECCV)
Conference on Neural Information Processing Systems (NeurIPS)
Association for the Advancement of Artificial Intelligence (AAAI)
International Conference on Medical Imaging Computing and Computer Assisted Intervention (MICCAI)
