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De Cheng
About Me
De Cheng
De Cheng is currently a Professor and doctoral supervisor with the School of Telecommunications Engineering, Xidian University, and a member of the ISN National Key Laboratory. He was formerly a Principal Engineer at Huawei. He received the B.S. degree in Jul. 2011 and the Ph.D. degree in Dec. 2017 from Xi'an Jiaotong University, where he was jointly trained with Carnegie Mellon University from 2015 to 2017. In Jan. 2021, he joined Xidian University as a recruited faculty member. His research interests include Embodied Intelligence and Agents, Multimodal Foundation Models, and Machine Learning.
He has published more than 100 papers, among which 80 are first/corresponding-author papers in CCF-A or CAS Q1 TOP journals and conferences. His Google Scholar citations exceed 4,500, with 2 ESI Highly Cited Papers, and a single first-author paper cited over 1,600 times. He has received the CCF-CV Rising Star Award, the Shaanxi Excellent Doctoral Dissertation Award, the Nissan (China) Scholarship, and Outstanding Doctoral Scholarships. He serves as Associate Editor for IEEE TIP, TNNLS, TMM, TCSVT, and TCSST, and as Area Chair / PC member for CVPR, ICCV, ECCV, AAAI, etc. He presides over the NSFC Youth and General Programs, a sub-project of the National Key R&D Program, and industry projects with the CCF-Huawei Poplar Fund, Zhejiang Lab, ByteDance, and Google.
Openings: I have openings for Master's and Ph.D. students (2027 intake, both recommendation-based and exam-based). Outstanding undergraduate interns are always welcome — please email me your CV and transcript; excellent interns may be recommended for postgraduate admission directly. Interns receive a monthly stipend, sufficient GPU resources, and hands-on research supervision. Recent master's graduates joined Huawei (3), ByteDance, Tencent, Xiaomi, and China Mobile, or continued Ph.D. study (2); one joined Xi'an University of Technology as a faculty member.
60
Journal/Conference
Publications
Selected Publications
2026
- De Cheng, Haichun Tai, Nannan Wang, Xiangqian Zhao, Jie Li, Xinbo Gao: A Multi-Granularity Scene-Aware Graph Convolution Method for Weakly Supervised Person Search. IJCV, 2026.
- Huaijie Wang, De Cheng, Lingfeng He, Yan Li, Jie Li, Nannan Wang, Xinbo Gao: EKPC: Elastic Knowledge Preservation and Compensation for Class-Incremental Learning. IJCV, 2026.
- Shizhou Zhang, Yue Lu, De Cheng, Yinghui Xing, Nannan Wang, Peng Wang, Yanning Zhang: VPT-NSP2++: Importance-Aware Visual Prompt Tuning in Null Space for Continual Learning. TPAMI, 2026.
- De Cheng, Yubo Li, Chaowei Fang, Shizhou Zhang, Nannan Wang, Xinbo Gao: Isolating Interference Factors for Robust Cloth-Changing Person Re-Identification. TPAMI, 2026.
- De Cheng, Zhipeng Xu, Xinyang Jiang, Dongsheng Li, Nannan Wang, Xinbo Gao: Prompt Disentanglement via Language Guidance and Representation Alignment for Domain Generalization. TPAMI, 2026.
- Chaowei Fang, Bolin Fu, De Cheng, Lechao Cheng, Dingwen Zhang: High-frequency structure transformer for magnetic resonance image super-resolution. PR, 2026.
- Weinan Zhao, Yanling Ji, Yan Li, De Cheng, Junwei Han, Dingwen Zhang: Learning task-shared and specific knowledge via mixture-of-experts in generative model for continual learning. PR, 2026.
- Chaowei Fang, Bolin Fu, Tao Yang, De Cheng: Improving face forgery detection via hierarchical mixture of experts and fine-grained visual-text alignment. PR, 2026.
- Xi Yang, Hexun Zhou, De Cheng, Menghui Tian, Nannan Wang: Semantic-Interactive Clustering Optimization With SAM for Weakly Supervised Person Search. TCSVT, 2026.
- Chaowei Fang, Bolin Fu, De Cheng, Chengpei Tang, Guanbin Li: Learning Prompt Adapters for Forgetting-Free Continual Image Super-Resolution. TIP, 2026.
- Yubin Wang, Xinyang Jiang, De Cheng, Dongsheng Li, Cairong Zhao: ActPrompt: In-Domain Feature Adaptation via Action Cues for Video Temporal Grounding. TIP, 2026.
- Xi Yang, Hexun Zhou, De Cheng, Nannan Wang: Overcoming Dual Incremental Challenges in Continual Person Search via Adapter and Prototype. TIP, 2026.
- Shibin Su, Guoqiang Liang, De Cheng, Shizhou Zhang, Lingyan Ran: Multi-Level Collaborative Distillation Meets Global Workspace Model: A Unified Framework for OCIL. TIP, 2026.
- Haonan Shi, Yubin Wang, De Cheng, Lingfeng He, Nannan Wang, Xinbo Gao: Hierarchical Identity Learning for Unsupervised Visible-Infrared Person Re-Identification. TIP, 2026.
- Chaowei Fang, Bolin Fu, De Cheng, Lechao Cheng, Guanbin Li: Dual-Domain Adaptation Networks for Realistic Image Super-Resolution. TMM, 2026.
- Qirui Wu, Shizhou Zhang, De Cheng, Yinghui Xing, Lingyan Ran, Dahu Shi, Peng Wang: Better Matching, Less Forgetting: A Quality-Guided Matcher for Transformer-based Incremental Object Detection. AAAI, 2026.
- Lingfeng He, De Cheng, Di Xu, Huaijie Wang, Nannan Wang: Harnessing Textual Semantic Priors for Knowledge Transfer and Refinement in CLIP-Driven Continual Learning. AAAI, 2026.
2025
- Lingfeng He, De Cheng, Nannan Wang, Xinbo Gao: Exploring Homogeneous and Heterogeneous Consistent Label Associations for Unsupervised Visible-Infrared Person ReID. IJCV, 2025.
- De Cheng, Lingfeng He, Nannan Wang, Dingwen Zhang, Xinbo Gao: Semantic-Aligned Learning with Collaborative Refinement for Unsupervised VI-ReID. IJCV, 2025.
- Yudong Liang, Shaoji Li, De Cheng, Wenjian Wang, Deyu Li, Jiye Liang: Image dehazing via self-supervised depth guidance. PR, 2025.
- Ruoyu Zhao, Mingrui Zhu, Shiyin Dong, De Cheng, Nannan Wang, Xinbo Gao: CatVersion: Concatenating Embeddings for Diffusion-Based Text-to-Image Personalization. TCSVT, 2025.
- De Cheng, Yusong Hu, Nannan Wang, Dingwen Zhang, Xinbo Gao: Achieving Plasticity-Stability Trade-Off in Continual Learning Through Adaptive Orthogonal Projection. TCSVT, 2025.
- De Cheng, Lei Wei, Chaowei Fang, Lingfeng He, Nannan Wang, Xinbo Gao: Progressive Feature-Attribute Matching via Bi-Directional Generation for Transductive Zero-Shot Learning. TCSVT, 2025.
- Shizhou Zhang, Wenlong Luo, De Cheng, Yinghui Xing, Guoqiang Liang, Peng Wang, Yanning Zhang: Prompt-Based Modality Alignment for Effective Multi-Modal Object Re-Identification. TIP, 2025.
- Wenjiao Dong, Xi Yang, De Cheng, Nannan Wang, Xinbo Gao: Escaping Modal Interactions: An Efficient DESANet for Multi-Modal Object Re-Identification. TIP, 2025.
- Guoqiang Liang, Shibin Su, De Cheng, Shizhou Zhang, Peng Wang, Yanning Zhang: Enhancing Feature Learning With Hard Samples in Mutual Learning for Online Class Incremental Learning. TIP, 2025.
- Xi Yang, Wenjiao Dong, Xian Wang, De Cheng, Nannan Wang: FA-Net: A Feature Alignment Network for Video-Based Visible-Infrared Person Re-Identification. TIP, 2025.
- Guozhang Li, Xinpeng Ding, De Cheng, Jie Li, Nannan Wang, Xinbo Gao: ETC: Temporal Boundary Expand Then Clarify for Weakly Supervised Video Grounding With Multimodal Large Language Model. TMM, 2025.
- Xiaoyan Sun, De Cheng, Yan Li, Nannan Wang, Dingwen Zhang, Xinbo Gao, Jiande Sun: Progressive Prompt-Driven Low-Light Image Enhancement With Frequency Aware Learning. TMM, 2025.
- Yi Liu, De Cheng, Dingwen Zhang, Shoukun Xu, Jungong Han: Capsule Networks With Residual Pose Routing. TNNLS, 2025.
- Xi Yang, Wenjiao Dong, De Cheng, Nannan Wang, Xinbo Gao: TIENet: A Tri-Interaction Enhancement Network for Multimodal Person Reidentification. TNNLS, 2025.
- Xi Yang, Jiachen Sun, Songsong Duan, De Cheng: Dual Information Purification for Lightweight SAR Object Detection. AAAI, 2025.
- Yue Lu, Shizhou Zhang, De Cheng, Guoqiang Liang, Yinghui Xing, Nannan Wang, Yanning Zhang: Training Consistent Mixture-of-Experts-Based Prompt Generator for Continual Learning. AAAI, 2025.
- Zhipeng Xu, De Cheng, Xinyang Jiang, Nannan Wang, Dongsheng Li, Xinbo Gao: Adversarial Domain Prompt Tuning and Generation for Single Domain Generalization. CVPR, 2025.
- Jiachen Sun, De Cheng, Xi Yang, Nannan Wang: Dual Domain Control via Active Learning for Remote Sensing Domain Incremental Object Detection. ICCV, 2025.
- Wenlong Luo, Shizhou Zhang, De Cheng, Yinghui Xing, Guoqiang Liang, Peng Wang, Yanning Zhang: Gradient Decomposition and Alignment for Incremental Object Detection. ICCV, 2025.
- Qirui Wu, Shizhou Zhang, De Cheng, Yinghui Xing, Di Xu, Peng Wang, Yanning Zhang: Demystifying Catastrophic Forgetting in Two-Stage Incremental Object Detector. ICML, 2025.
- Chaowei Fang, Hangfei Ma, Zhihao Li, De Cheng, Yue Zhang, Guanbin Li: Screening, Rectifying, and Re-Screening: A Unified Framework for Tuning Vision-Language Models with Noisy Labels. IJCAI, 2025.
- Guoqiang Liang, Chuan Qin, De Cheng, Shizhou Zhang, Yanning Zhang: Boosting Multi-Modal Alignment: Geometric Feature Separation for Class Incremental Learning. ACM MM, 2025.
- Long Chen, De Cheng, Shizhou Zhang, Yinghui Xing, Di Xu, Yanning Zhang: Amplitude-aware Domain Style Replay for Lifelong Person Re-identification. ACM MM, 2025.
2024
- Peiliang Huang, Dingwen Zhang, De Cheng, Longfei Han, Pengfei Zhu, Junwei Han: M-RRFS: A Memory-Based Robust Region Feature Synthesizer for Zero-Shot Object Detection. IJCV, 2024.
- De Cheng, Yuxin Zhao, Nannan Wang, Guozhang Li, Dingwen Zhang, Xinbo Gao: Efficient Statistical Sampling Adaptation for Exemplar-Free Class Incremental Learning. TCSVT, 2024.
- De Cheng, Haichun Tai, Nannan Wang, Chaowei Fang, Xinbo Gao: Neighbor Consistency and Global-Local Interaction: A Novel Pseudo-Label Refinement Approach for Unsupervised Person Re-Identification. TIFS, 2024.
- Guozhang Li, De Cheng, Nannan Wang, Jie Li, Xinbo Gao: Neighbor-Guided Pseudo-Label Generation and Refinement for Single-Frame Supervised Temporal Action Localization. TIP, 2024.
- Yinghui Xing, Qirui Wu, De Cheng, Shizhou Zhang, Guoqiang Liang, Peng Wang, Yanning Zhang: Dual Modality Prompt Tuning for Vision-Language Pre-Trained Model. TMM, 2024.
- De Cheng, Yanling Ji, Dong Gong, Yan Li, Nannan Wang, Junwei Han, Dingwen Zhang: Continual All-in-One Adverse Weather Removal With Knowledge Replay on a Unified Network Structure. TMM, 2024.
- De Cheng, Yan Li, Dingwen Zhang, Nannan Wang, Jiande Sun, Xinbo Gao: Progressive Negative Enhancing Contrastive Learning for Image Dehazing and Beyond. TMM, 2024.
- Guozhang Li, De Cheng, Xinpeng Ding, Nannan Wang, Jie Li, Xinbo Gao: Weakly Supervised Temporal Action Localization With Bidirectional Semantic Consistency Constraint. TNNLS, 2024.
- Yubin Wang, Xinyang Jiang, De Cheng, Dongsheng Li, Cairong Zhao: Learning Hierarchical Prompt with Structured Linguistic Knowledge for Vision-Language Models. AAAI, 2024.
- De Cheng, Zhipeng Xu, Xinyang Jiang, Nannan Wang, Dongsheng Li, Xinbo Gao: Disentangled Prompt Representation for Domain Generalization. CVPR, 2024.
- Xiaoyan Sun, Yan Li, De Cheng, Dingwen Zhang, Ling Gao, Luofeng Zhai, Jiande Sun: Gradient and Brightness Guided Low-Light Enhancement with Attention-Based Self-Paced Learning. ICASSP, 2024.
- Yusong Hu, De Cheng, Dingwen Zhang, Nannan Wang, Tongliang Liu, Xinbo Gao: Task-aware Orthogonal Sparse Network for Exploring Shared Knowledge in Continual Learning. ICML, 2024.
- Haichun Tai, De Cheng, Jie Li, Nannan Wang, Xinbo Gao: Multi-Granularity Graph-Convolution-Based Method for Weakly Supervised Person Search. IJCAI, 2024.
- Yubo Li, De Cheng, Chaowei Fang, Changzhe Jiao, Nannan Wang, Xinbo Gao: Disentangling Identity Features from Interference Factors for Cloth-Changing Person Re-identification. ACM MM, 2024.
- Xi Yang, Huanling Liu, De Cheng, Nannan Wang, Xinbo Gao: Feature-Level Adversarial Attacks and Ranking Disruption for Visible-Infrared Person Re-identification. NeurIPS, 2024.
- Yue Lu, Shizhou Zhang, De Cheng, Yinghui Xing, Nannan Wang, Peng Wang, Yanning Zhang: Visual Prompt Tuning in Null Space for Continual Learning. NeurIPS, 2024.
- Ying Yang, De Cheng, Chaowei Fang, Yubiao Wang, Changzhe Jiao, Lechao Cheng, Nannan Wang, Xinbo Gao: Diffusion-based Layer-wise Semantic Reconstruction for Unsupervised Out-of-Distribution Detection. NeurIPS, 2024.