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 README.md. [ENGLISH/CHINESE]
Deep Relative Distance Learning: Tell the Difference Between Similar Vehicles
- Hongye Liu, Yonghong Tian*, Yaowei Wang*, Lu Pang, Tiejun Huang
- CVPR 2016
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
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
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)
- 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: https://spikingjelly.readthedocs.io.
- For an introduction to the project, see the README.md.