Publications

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

• Variational Rectification Inference for Learning with Noisy Labels [URL][Code]
  Haoliang Sun#, Qi Wei#, Lei Feng, Yupeng Hu, Fan Liu, Hehe Fan, Yilong Yin
  International Journal of Computer Vision (IJCV), 2024.

• 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.