most citedSpiking PointNet: Spiking Neural Networks for Point Clouds

16 citations · 33 across the 8 of their papers we have counts for

collaborators

8 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.RO20232 cited

Sequential Dexterity: Chaining Dexterous Policies for Long-Horizon Manipulation

Yuanpei Chen, Chen Wang, Li Fei-Fei +1

Many real-world manipulation tasks consist of a series of subtasks that are significantly different from one another. Such long-horizon, complex tasks highlight the potential of de…

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.RO20236 cited

Dynamic Handover: Throw and Catch with Bimanual Hands

Binghao Huang, Yuanpei Chen, Tianyu Wang +4

Humans throw and catch objects all the time. However, such a seemingly common skill introduces a lot of challenges for robots to achieve: The robots need to operate such dynamic ac…

cs.NE2023

InfLoR-SNN: Reducing Information Loss for Spiking Neural Networks

Yufei Guo, Yuanpei Chen, Liwen Zhang +5

The Spiking Neural Network (SNN) has attracted more and more attention recently. It adopts binary spike signals to transmit information. Benefitting from the information passing pa…

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…