方超伟  |  副教授  |  青年拔尖人才支持计划（B类）
智能感知实验室(负责人：祝继华教授) · 软件学院 · 西安交通大学

研究方向：多模态信息处理与表示、鲁棒机器学习、医学影像分析，课题组专注于如何从不可靠的数据中学习可靠的知识，并倡导非暴力沟通。

教育背景：
香港大学 计算机科学博士（2015–2019），导师：俞益洲教授
西安交通大学 控制科学与工程（2013–2015）
西安交通大学 自动化专业学士（2009–2013）

工作经历：
2026年4月至今：西安交通大学软件学院 副教授（青年拔尖人才B类）
2023年3月–2026年3月：西安电子科技大学人工智能学院 副教授（华山学者）

科研成果：
在 IEEE TPAMI、TIP、TMI、TNNLS、Pattern Recognition 等国际权威期刊及 CVPR、ICCV、NeurIPS、ICML、AAAI、ACM MM 等顶级会议发表论文60余篇。主持国家自然科学基金面上项目/青年项目、华为昇腾创新模型开发等科研项目多项。

代表性论文：
* 通讯作者，† 共同第一作者
[1] Fang C, Fu B, Yang T, Cheng D. Improving Face Forgery Detection via Hierarchical Mixture of Experts and Fine-grained Visual-Text Alignment. Pattern Recognition, 2026.
[2] Fang C, Fu B, Cheng D, Tang C, Li G. Learning Prompt Adapters for Forgetting-Free Continual Image Super-resolution. IEEE Transactions on Image Processing, 2026.
[3] Cheng D, Li Y, Fang C*, Zhang S, Wang N, Gao X. Isolating Interference Factors for Robust Cloth-Changing Person Re-Identification. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2026.
[4] Fang C, Fu B, Cheng D, Cheng L, Li G. Dual-domain Adaptation Networks for Realistic Image Super-resolution. IEEE Transactions on Multimedia, 2025.
[5] Chen J, Fang C*, Li J, Leng Y, Li G*. Decouple and Couple: Exploiting Prior Knowledge for Visible Video Watermark Removal. IEEE Transactions on Image Processing, 2025.
[6] Mo Z, Chen J, Fang C*, Li G*. PatchWiper: Leveraging Dynamic Patch-Wise Parameters for Real-World Visible Watermark Removal. Proceedings of the ACM International Conference on Multimedia (ACM MM), 2025.
[7] Fang C, Liao Z, Yu Y. Piecewise Flat Embedding for Image Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018, 41(6): 1470-1485.
[8] Fang C, Li G, Han X, Yu Y. Self-enhanced Convolutional Network for Facial Video Hallucination. IEEE Transactions on Image Processing, 2019, 29: 3078-3090.
[9] Fang C†, Wang Q†, Cheng L, Gao Z, Pan C, Cao Z, Zheng Z, Zhang D. Reliable Mutual Distillation for Medical Image Segmentation under Imperfect Annotations. IEEE Transactions on Medical Imaging, 2023. (Highly Cited Paper)
[10] Fang C†, Tian H†, Zhang D, Zhang Q, Han J, Han J. Densely Nested Top-down Flows for Salient Object Detection. Science China Information Sciences, 2022, 65(8). (Hot Paper)
[11] Fang C, Ma H, Li Z, Cheng D, Zhang Y, Li G. Screening, Rectifying, and Re-Screening: A Unified Framework for Tuning Vision-Language Models with Noisy Labels. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2025.
[12] Fang C, Zhou Z, Chen J, Su H, Wu Q, Li G. Variance-Insensitive and Target-Preserving Mask Refinement for Interactive Image Segmentation. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024.
[13] Fang C, Zhang D, Wang L, Zhang Y, Cheng L, Han J. Cross-Modality High-Frequency Transformer for MR Image Super-Resolution. Proceedings of the ACM Conference on Multimedia (ACM MM), 2022.
[14] Fang C†, Wang L†, Zhang D, Xu J, Yuan Y, Han J. Incremental Cross-view Mutual Distillation for Self-supervised Medical CT Synthesis. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
[15] Fang C, Cheng L, Mao Y, Zhang D, Fang Y, Li G, Qi H, Jiao L. Separating Noisy Samples from Tail Classes for Long-tailed Image Classification with Label Noise. IEEE Transactions on Neural Networks and Learning Systems, 2023.
[16] Fang C†, Li X†, Li Z, Jiao L, Zhang D. Interactive Dual-Model Learning for Semi-supervised Medical Image Segmentation. 自动化学报, 2023.
[17] Zhao G†, Fang C†, Li G, Jiao L, Yu Y. Contralaterally Enhanced Networks for Thoracic Disease Detection. IEEE Transactions on Medical Imaging, 2021, 40(9): 2428-2438.
[18] Huang J†, Fang C†, Chen W, Chai Z, Wei X, Wei P, Lin L, Li G. Trash to Treasure: Harvesting OOD Data with Cross-Modal Matching for Open-Set Semi-Supervised Learning. Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2021.
[19] Nie Y†, Fang C†, Cheng L, Lin L, Li G. Adapting Object Size Variance and Class Imbalance for Semi-Supervised Object Detection. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2023. (Oral)
[20] Yang Y†, Cheng D†*, Fang C†*, Wang Y, Jiao C, Cheng L, Wang N, Gao X. Diffusion-based Layer-wise Semantic Reconstruction for Unsupervised Out-of-Distribution Detection. Proceedings of the Conference on Neural Information Processing Systems (NeurIPS), 2024.

学术服务：
担任 CVPR、ICCV、ECCV、NeurIPS、ICML、AAAI、ACM MM 等国际顶级会议审稿人；IEEE TIP、TMI、TNNLS、Pattern Recognition 等国际期刊审稿人；ACM MM 2022 "以人为中心的多媒体分析"国际研讨会程序共同主席。

联系方式：
地址：陕西省西安市碑林区咸宁西路28号，西安交通大学软件学院
邮箱： chaoweifang AT outlook.com
个人主页：chaoweifang.github.io
Google Scholar：https://scholar.google.com/citations?user=eNtYEmcAAAAJ&hl=en