Chenchen Jing

Chenchen Jing

Ph.D. Candidate

Chenchen Jing (景宸琛)

Short Bio

I am a postdoctoral research fellow of Zhejiang University, working with Prof. Chunhua Shen and Prof. Hao Chen. I received my Ph.D. degree of Beijing Institute of Technology (BIT), advised by Prof. Yuwei Wu and Prof. Yunde Jia. I also collaborate with Prof. Qi Wu of the University of Adelaide. Prior to the Ph.D. study, I received the B.S. degree in computer science in 2016 from the BIT. My research area lies at the intersection of computer vision and natural language processing.

Recent Publications

  1. Chenchen Jing, Yukun Li, Hao Chen, and Chunhua Shen. Retrieval-augmented Primitive Representations for Compositional Zero-shot Learning. In Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI’24), 2024.
  2. Muzhi Zhu, Hengtao Li, Hao Chen, Chengxiang Fan, Weian Mao, Chenchen Jing, Yifan Liu, Chunhua Shen. SegPrompt: Boosting Open-world Segmentation via Category-level Prompt Learning. In Proceedings of the IEEE Conference on Computer Vision (ICCV’23), 2023. [pdf]
  3. Chuanhao Li, Zhen Li, Chenchen Jing, Yunde Jia, Yuwei Wu. Exploring the Effect of Primitives for Compositional Generalization in Vision-and-Language. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR’23), 2023. [pdf]

First-author Publications

  1. Chenchen Jing, Yukun Li, Hao Chen, and Chunhua Shen. Retrieval-augmented Primitive Representations for Compositional Zero-shot Learning. In Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI’24), 2024.
  2. Chenchen Jing, Yunde Jia, Yuwei Wu, Xinyu Liu and Qi Wu. Maintaining Reasoning Consistency in Compositional Visual Question Answering. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR’22), 2022. [pdf]
  3. Chenchen Jing, Yunde Jia, Yuwei Wu, Chuanhao Li and Qi Wu. Learning the Dynamics of Visual Relational Reasoning via Reinforced Path Routing. In Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI’22), 2022. [pdf]
  4. Chenchen Jing, Yuwei Wu, Mingtao Pei, Yao Hu, Yunde Jia and Qi Wu. Visual-Semantic Graph Matching for Visual Grounding. In Proceedings of the 28th ACM International Conference on Multimedia (MM ’20), 2020. [pdf]
  5. Chenchen Jing, Yuwei Wu, Xiaoxun Zhang, Yunde Jia and Qi Wu. Overcoming Language Priors in VQA via Decomposed Linguistic Representations. In Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI’20), 2020. [pdf]
  6. Chenchen Jing, Zhen Dong, Mingtao Pei and Yunde Jia. Heterogeneous Hashing Network for Face Retrieval across Image and Video Domains. IEEE Transactions on Multimedia (T-MM), 2019. [pdf]

Co-author Publications

  1. Muzhi Zhu, Hengtao Li, Hao Chen, Chengxiang Fan, Weian Mao, Chenchen Jing, Yifan Liu, Chunhua Shen. SegPrompt: Boosting Open-world Segmentation via Category-level Prompt Learning. In Proceedings of the IEEE Conference on Computer Vision (ICCV’23), 2023. [pdf]
  2. Chuanhao Li, Zhen Li, Chenchen Jing, Yunde Jia, Yuwei Wu. Exploring the Effect of Primitives for Compositional Generalization in Vision-and-Language. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR’23), 2023. [pdf]
  3. Qingsheng Wang, Lingqiao Liu, Chenchen Jing, Hao Chen, Guoqiang Liang, Peng Wang, Chunhua Shen. Learning Conditional Attributes for Compositional Zero-Shot Learning. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR’23), 2023. [pdf]
  4. Mingliang Zhai, Chuanhao Li, Chenchen Jing, Yuwei Wu. Synthesizing Counterfactual Samples for Overcoming Moment Biases in Temporal Video Grounding. In Proceedings of the Pattern Recognition and Computer Vision (PRCV’22), 2022. [pdf]
  5. Wei Jiang, Yuwei Wu, Chenchen Jing, Tan Yu and Yunde Jia. Unsupervised Deep Quantization for Object Instance Search. Neurocomputing, 2019. [pdf]
  6. Zhen Dong, Chenchen Jing, Mingtao Pei and Yunde Jia. Deep CNN based binary hash video representations for face retrieval. Pattern Recognition (PR), 2018. [pdf]