Jianyuan
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Jianyuan Guo (郭健元)

I am a PhD candidate in the School of Computer Science, The University of Sydney. I am supervised by Prof. Chang Xu. I obtained the B.S. and M.S. from the school of EECS, Peking University at 2017 and 2020, supervised by Prof. Chao Zhang. My main research interest lies in machine perception algorithms and their related applications, including efficient neural network (e.g., CNN and Transformer) in computer vision and natural language processing, self-supervised learning, neural architecture search, multimodal fusion, and LLM for AGI.

Email  /  Google Scholar  /  Github  /  DBLP

News

  • 05/2024, 2 papers are accepted by ICML 2024.

  • 02/2024, Great honor to join the AAAI Student Committee.

  • 02/2024, We release the code of Data efficient Large Vision Model (DeLVM).

  • 10/2023, 4 papers are accepted by NeurIPS 2023.

  • 03/2022, 5 papers are accepted by CVPR 2022.

  • 09/2022, 4 papers are accepted by NeurIPS 2022.

    • Selected Publications

  • Data-efficient Large Vision Models through Sequential Autoregression.
    Jianyuan Guo*, Zhiwei Hao*, Chengcheng Wang*, Yehui Tang, Han Wu, Han Hu, Kai Han, Chang Xu
    ICML 2024 | paper | code

  • GeminiFusion: Efficient Pixel-wise Multimodal Fusion for Vision Transformer.
    Ding Jia*, Jianyuan Guo*, Kai Han, Han Wu, Chao Zhang, Chang Xu, Xinghao Chen
    ICML 2024 | paper | code

  • PrimKD: Primary Modality Guided Multimodal Fusion for RGB-D Semantic Segmentation.
    Zhiwei, Hao, Zhongyu Xiao, Yong Luo, Jianyuan Guo†, Jing Wang, Li Shen, Han Hu
    ACM MM 2024 | paper

  • Token Compensator: Altering Inference Cost of Vision Transformer without Re-Tuning.
    Shibo Jie, Yehui Tang, Jianyuan Guo, Zhi-Hong Deng, Kai Han, Yunhe Wang
    ECCV 2024 | paper

  • Revisit the Power of Vanilla Knowledge Distillation from Small Scale to Large Scale.
    Zhiwei Hao*, Jianyuan Guo*, Kai Han, Han Hu, Chang Xu, Yunhe Wang
    NeurIPS 2023 | paper | code

  • One-for-All: Bridge the Gap Between Heterogeneous Architectures in Knowledge Distillation.
    Zhiwei Hao, Jianyuan Guo, Kai Han, Yehui Tang, Han Hu, Yunhe Wang, Chang Xu
    NeurIPS 2023 | paper | code

  • VanillaNet: the Power of Minimalism in Deep Learning.
    Hanting Chen, Yunhe Wang, Jianyuan Guo, Dacheng Tao
    NeurIPS 2023 | paper | code

  • Hierarchical relational learning for few-shot knowledge graph completion.
    Han Wu, Jie Yin, Bala Rajaratnam, Jianyuan Guo
    ICLR 2023 | paper | code

  • Hire-MLP: Vision MLP via Hierarchical Rearrangement.
    Jianyuan Guo*, Yehui Tang*, Kai Han, Xinghao Chen, Han Wu, Chao Xu, Chang Xu, Yunhe Wang
    CVPR 2022 | paper | code

  • CMT: Convolutional Neural Networks Meet Vision Transformers.
    Jianyuan Guo, Kai Han, Han Wu, Chang Xu, Yehui Tang, Chunjing Xu, Yunhe Wang
    CVPR 2022 | paper | code

  • An Image Patch is a Wave: Quantum Inspired Vision MLP (WaveMLP).
    Yehui Tang, Kai Han, Jianyuan Guo, Chang Xu, Yanxi Li, Chao Xu, Yunhe Wang
    CVPR 2022 | paper | code

  • Brain-inspired Multilayer Perceptron with Spiking Neurons.
    Wenshuo Li, Hanting Chen, Jianyuan Guo, Ziyang Zhang, Yunhe Wang
    CVPR 2022 | paper

  • Learning efficient vision transformers via fine-grained manifold distillation.
    Zhiwei Hao, Jianyuan Guo, Ding Jia, Kai Han, Yehui Tang, Chao Zhang, Han Hu, Yunhe Wang
    NeurIPS 2022 | paper

  • Positive-Unlabeled Data Purification in the Wild for Object Detection.
    Jianyuan Guo, Kai Han, Han Wu, Chao Zhang, Xinghao Chen, Chunjing Xu, Chang Xu, Yunhe Wang
    CVPR 2021 | paper

  • Distilling object detectors via decoupled features.
    Jianyuan Guo, Kai Han, Yunhe Wang, Han Wu, Xinghao Chen, Chunjing Xu, Chang Xu
    CVPR 2021 | paper | code

  • Transformer in Transformer.
    Kai Han, An Xiao, Enhua Wu, Jianyuan Guo, Chunjing Xu, Yunhe Wang
    NeurIPS 2021 | paper | code

  • Hit-detector: Hierarchical trinity architecture search for object detection.
    Jianyuan Guo, Kai Han, Yunhe Wang, Chao Zhang, Zhaohui Yang, Han Wu, Xinghao Chen, Chang Xu
    CVPR 2020 | paper | code

  • Ghostnet: More features from cheap operations.
    Kai Han, Yunhe Wang, Qi Tian, Jianyuan Guo, Chunjing Xu, Chang Xu
    CVPR 2020 | paper | code

  • Beyond human parts: Dual part-aligned representations for person re-identification.
    Jianyuan Guo, Yuhui Yuan, Lang Huang, Chao Zhang, Jin-Ge Yao, Kai Han
    ICCV 2019 | paper | code

  • Attribute-aware attention model for fine-grained representation learning.
    Kai Han*, Jianyuan Guo*, Chao Zhang, Mingjian Zhu
    ACM MM 2018 | paper | code

  • A Survey on Vision Transformer
    Kai Han, Yunhe Wang, Hanting Chen, Xinghao Chen, Jianyuan Guo, Zhenhua Liu, Yehui Tang, An Xiao, Chunjing Xu, Yixing Xu, Zhaohui Yang, Yiman Zhang, Dacheng Tao
    IEEE T-PAMI 2022 | paper

  • OCNet: Object context for semantic segmentation
    Yuan Yuhui, Lang Huang, Jianyuan Guo, Chao Zhang, Xilin Chen, Jingdong Wang
    IJCV 2021 | paper

  • GhostNets on Heterogeneous Devices via Cheap Operations
    Kai Han, Yunhe Wang, Chang Xu, Jianyuan Guo, Chunjing Xu, Enhua Wu, Qi Tian
    IJCV 2021 | paper

    • Services

  • Student member in the AAAI Student Committee.

  • Conference Area Chair of ICLR 2025.

  • Conference Reviewers of CVPR, ICCV, ECCV, ICLR, ICML, AAAI, NeurIPS, etc.

  • Journal Reviewers of TPAMI, IJCV, TIP, Pattern Recognition, Neurocomputing, TMLR, etc.

    • Selected Awards

  • 2022, Google PhD Fellowship

  • 2022, Australian Government RTP Scholarship.

  • 2020, Excellent Graduate, Peking University.

  • 2018-2019, Award for Scientific Research, Peking University.

  • 2017-2018, Award for Scientific Research & Benz Scholarship, Peking University.

  • 2017, Graduate Scholarship, Peking University.

    • This website is based on the source code shared by Dr. Yunhe Wang. Thanks.