Publications

[Google Scholar]
(# denotes equal contribution, * denotes corresponding author)

  • Learning Sample-Aware Threshold for Semi-Supervised Learning [URL]
    Qi Wei, Lei Feng, Haoliang Sun*, Ren Wang, Rundong He, Yilong Yin
    Machine Learning, 2023 (ACML Journal Track).

  • Attentional Prototype Inference for Few-Shot Segmentation [arXiv] [Code]
    Haoliang Sun, Xiankai Lu, Haochen Wang, Yilong Yin, Xiantong Zhen, Cees G. M. Snoek, Ling Shao
    Pattern Recognition (PR), 2023.

  • MetaViewer: Towards A Unified Multi-View Representation [arXiv]
    Ren Wang, Haoliang Sun*, Yuling Ma, Xiaoming Xi, Yilong Yin
    In proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.

  • Fine-Grained Classification with Noisy Labels [arXiv]
    Qi Wei, Lei Feng, Haoliang Sun*, Ren Wang, Chenhui Guo, Yilong Yin
    In proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.

  • 面向标签噪声学习的联合训练框架 [URL]
    魏琦, 孙皓亮*, 马玉玲,尹义龙
    中国科学: 信息科学, 2023.

  • Self-Filtering: A Noise-Aware Sample Selection for Label Noise with Confidence Penalization [arXiv]
    Qi Wei, Haoliang Sun*, Xiankai Lu, Yilong Yin
    In proc. of European Conference on Computer Vision (ECCV), 2022.

  • Towards Accurate and Robust Domain Adaptation Under Multiple Noisy Environments [pdf]
    Zhongyi Han, Xian-Jin Gui, Haoliang Sun, Yilong Yin, Shuo Li
    IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2022.

  • Learning Transferable Parameters for Unsupervised Domain Adaptation [arXiv]
    Zhongyi Han, Haoliang Sun, Yilong Yin
    IEEE Transactions on Image Processing, 2022.

  • MetaKernel: Learning Variational Random Features with Limited Labels [arXiv]
    Yingjun Du, Haoliang Sun, Xiantong Zhen, Jun Xu, Yilong Yin, Ling Shao, Cees GM Snoek
    IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2022.

  • SNIP-FSL: Finding Task-Specific Lottery Jackpots for Few-Shot Learning [URL]
    Ren Wang, Haoliang Sun, Xiushan Nie, Yilong Yin
    Knowledge-Based Systems (KBS), 2022.

  • Learning to Rectify for Robust Learning with Noisy Labels [arXiv] [Code]
    Haoliang Sun#, Chenhui Guo#, Qi Wei, Zhongyi Han, and Yilong Yin
    Pattern Recognition (PR), 2021.

  • Learning to Learn Kernels with Variational Random Features [arXiv [Code]
    Xiantong Zhen#, Haoliang Sun#, Yingjun Du#, Jun Xu, Yilong Yin, Ling Shao, Cees Snoek
    In proc. of International Conference on Machine Learning (ICML), 2020.

  • DUAL-GLOW: Conditional Flow-Based Generative Model for Modality Transfer [arXiv] [Code]
    Haoliang Sun, Ronak Mehta, Hao H. Zhou, Zhichun Huang, Sterling C. Johnson, Vivek Prabhakaran, Vikas Singh
    In proc. of IEEE International Conference on Computer Vision (ICCV), 2019.

  • Learning the Set Graphs: Image-Set Classification Using Sparse Graph Convolutional Networks [arXiv]
    Haoliang Sun, Xiantong Zhen, and Yilong Yin
    In proc. of IEEE International Conference on Image Processing (ICIP), 2019.

  • Modality-specific Structure Pre-serving Hashing for Cross-modal retrieval [URL]
    Xingbo Liu, Xiushan Nie, Haoliang Sun, Chaoran Cui, Yilong Yin
    In proc. of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2018.

  • Learning Deep Match Kernels for Image-Set Classification [pdf]
    Haoliang Sun, Xiantong Zhen, Yuanjie Zheng, Gongping Yang, Yilong Yin, and Shuo Li
    In proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.

  • Directly Estimating Spinal Cobb Angles by Structured Multi-Output Regression [arXiv]
    Haoliang Sun, Xiantong Zhen, Chris Bailey, Parham Rasoulinejad, Yilong Yin, and Shuo Li
    International Conference on Information Processing in Medical Imaging (Oral Paper, IPMI), 2017.