Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks

  • Wei Fang, Zhaofei Yu, Yanqi Chen, Timothée Masquelier, Tiejun Huang and Yonghong Tian*
  • ICCV 2021
  • For an introduction to the paper, see the [ENGLISH/CHINESE]

[PDF] [Code]


Deep Relative Distance Learning: Tell the Difference Between Similar Vehicles

  • Hongye Liu, Yonghong Tian*, Yaowei Wang*, Lu Pang, Tiejun Huang
  • CVPR 2016

[PDF] [Code]


Unsupervised Cross-Dataset Transfer Learning for Person Re-identification

  • Peixi Peng, Tao Xiang, Yaowei Wang, Massimiliano Pontil, Shaogang Gong, Tiejun Huang, Yonghong Tian*
  • CVPR 2016

[PDF] [Code]


Learning Complementary Saliency Priors for Foreground Object Segmentation in Complex Scenes

  • Yonghong Tian, Jia Li, Shui Yu, Tiejun Huang
  • Int’l Journal of Computer Vision, 111(2), Jan 2015, 153-170. 10.1007/s11263-014-0737-1

[PDF] [Code]


Image Saliency Estimation via Random Walk Guided by Informativeness and Latent Signal Correlations

  • Jia Li, Shu Fang (first co-author), Yonghong Tian*, Tiejun Huang, and Xiaowu Chen
  • Signal Processing: Image Communication, (2015)

[PDF] [Code]




  • SpikingJelly is an open-source deep learning framework for Spiking Neural Network (SNN) based on PyTorch.
  • The documentation of SpikingJelly is written in both English and Chinese:
  • For an introduction to the project, see the

[OpenI] [Github]