NeuroZoom: Denoising and Super Resolving Neuromorphic Events and Spikes. - Peiqi Duan; Yi Ma 001; Xinyu Zhou; Xinyu Shi 004; Zihao W. Wang; Tiejun Huang 001; Boxin Shi (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

SpikingResformer: Bridging ResNet and Vision Transformer in Spiking Neural Networks. - Xinyu Shi 004; Zecheng Hao; Zhaofei Yu (CVPR, 2024)

Threaten Spiking Neural Networks through Combining Rate and Temporal Information. - Zecheng Hao; Tong Bu; Xinyu Shi 004; Zihan Huang; Zhaofei Yu; Tiejun Huang 001 (ICLR, 2024)

A Progressive Training Framework for Spiking Neural Networks with Learnable Multi-hierarchical Model. - Zecheng Hao; Xinyu Shi 004; Zihan Huang; Tong Bu; Zhaofei Yu; Tiejun Huang 001 (ICLR, 2024)

Towards High-performance Spiking Transformers from ANN to SNN Conversion. - Zihan Huang; Xinyu Shi 004; Zecheng Hao; Tong Bu; Jianhao Ding; Zhaofei Yu; Tiejun Huang 001 (ACM Multimedia, 2024)

LM-HT SNN: Enhancing the Performance of SNN to ANN Counterpart through Learnable Multi-hierarchical Threshold Model. - Zecheng Hao; Xinyu Shi 004; Yujia Liu 005; Zhaofei Yu; Tiejun Huang 001 (NeurIPS, 2024)

LM-HT SNN: Enhancing the Performance of SNN to ANN Counterpart through Learnable Multi-hierarchical Threshold Model. - Zecheng Hao; Xinyu Shi 004; Zhiyu Pan; Yujia Liu 005; Zhaofei Yu; Tiejun Huang 001 (CoRR, 2024)