most citedSpiking PointNet: Spiking Neural Networks for Point Clouds

16 citations · 25 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Technique Report of CVPR 2024 PBDL Challenges

Ying Fu, Yu Li, Shaodi You +96

The intersection of physics-based vision and deep learning presents an exciting frontier for advancing computer vision technologies. By leveraging the principles of physics to info…

cs.CV202316 cited

Spiking PointNet: Spiking Neural Networks for Point Clouds

Dayong Ren, Zhe Ma, Yuanpei Chen +4

Recently, Spiking Neural Networks (SNNs), enjoying extreme energy efficiency, have drawn much research attention on 2D visual recognition and shown gradually increasing application…

cs.CV20235 cited

Membrane Potential Batch Normalization for Spiking Neural Networks

Yufei Guo, Yuhan Zhang, Yuanpei Chen +5

As one of the energy-efficient alternatives of conventional neural networks (CNNs), spiking neural networks (SNNs) have gained more and more interest recently. To train the deep mo…

cs.CV20234 cited

RMP-Loss: Regularizing Membrane Potential Distribution for Spiking Neural Networks

Yufei Guo, Xiaode Liu, Yuanpei Chen +5

Spiking Neural Networks (SNNs) as one of the biology-inspired models have received much attention recently. It can significantly reduce energy consumption since they quantize the r…

cs.CV2023

Joint A-SNN: Joint Training of Artificial and Spiking Neural Networks via Self-Distillation and Weight Factorization

Yufei Guo, Weihang Peng, Yuanpei Chen +4

Emerged as a biology-inspired method, Spiking Neural Networks (SNNs) mimic the spiking nature of brain neurons and have received lots of research attention. SNNs deal with binary s…