[期刊论文] C. Zhu and Y. Peng, “A Boosted Multi-Task Model for Pedestrian Detection with Occlusion Handling”, IEEE Transactions on Image Processing (T-IP), 2015, Vol.24, No.12, pp.5619-5629. (SCI 1区，CCF-A类).

[期刊论文] C. Zhu, C.-E. Bichot and L. Chen, “Image Region Description Using Orthogonal Combination of Local Binary Patterns Enhanced with Color Information”, Pattern Recognition (PR), 2013, Vol.46, No.7, pp.1949-1963. (SCI 1区，CCF-B类).

[期刊论文] Y. Ma, M. Liu, C. Zhu* and X.-C. Yin, “HA-FGOVD: Highlighting Fine-Grained Attributes via Explicit Linear Composition for Open-Vocabulary Object Detection”, IEEE Transactions on Multimedia (T-MM), 2025, Vol.27, pp. 3171-3183. (SCI 1区，CCF-A类).

[期刊论文] Y. He, C. Zhu* and X.-C. Yin, “Occluded Pedestrian Detection via Distribution-Based Mutual-Supervised Feature Learning”, IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2022, Vol.23, No.8, pp. 10514-10529. (SCI 1区，CCF-B类).

[期刊论文] D. Huang, C. Zhu, Y. Wang and L. Chen, “HSOG: A Novel Local Image Descriptor Based on Histograms of the Second-Order Gradients”, IEEE Transactions on Image Processing (T-IP), 2014, Vol. 23, No. 11, pp.4680-4695. (SCI 1区，CCF-A类).

[期刊论文] C. Zhu and Y. Peng, “Discriminative Latent Semantic Feature Learning for Pedestrian Detection”, Neurocomputing, 2017, Vol.238, pp.126-138. (SCI 2区).

[会议论文] C. Zhu and Y. Peng, “Group Cost-Sensitive Boosting for Multi-Resolution Pedestrian Detection”, in Proc. of 30th AAAI Conference on Artificial Intelligence (AAAI), 2016, pp.3676-3682. (CCF-A类, oral).

[会议论文] C. Zhu and Y. Peng, “A Boosted Multi-Task Model for Pedestrian Detection with Occlusion Handling”, in Proc. of 29th AAAI Conference on Artificial Intelligence (AAAI), 2015, pp.3878-3884. (CCF-A类, oral).

[会议论文] M. Liu, C. Zhu*, et al, “Unsupervised Multi-view Pedestrian Detection”, in Proc. of 32nd ACM International Conference on Multimedia (ACM MM), 2024, pp. 1034-1042. (CCF-A类).

[会议论文] M. Liu, J. Jiang, C. Zhu* and X.-C. Yin, “VLPD: Context-Aware Pedestrian Detection via Vision-Language Semantic Self-Supervision”, in Proc. of IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023, pp.6662-6671. (CCF-A类).