88 citations · 140 across the 28 of their papers we have counts for
28 papers
Inter-event Interval Microscopy for Event Cameras
Changqing Su, Yanqin Chen, Zihan Lin +5
Event cameras, an innovative bio-inspired sensor, differ from traditional cameras by sensing changes in intensity rather than directly perceiving intensity and recording these vari…
Rethinking High-speed Image Reconstruction Framework with Spike Camera
Kang Chen, Yajing Zheng, Tiejun Huang +1
Spike cameras, as innovative neuromorphic devices, generate continuous spike streams to capture high-speed scenes with lower bandwidth and higher dynamic range than traditional RGB…
Differential Coding for Training-Free ANN-to-SNN Conversion
Zihan Huang, Wei Fang, Tong Bu +6
Spiking Neural Networks (SNNs) exhibit significant potential due to their low energy consumption. Converting Artificial Neural Networks (ANNs) to SNNs is an efficient way to achiev…
Towards High-performance Spiking Transformers from ANN to SNN Conversion
Zihan Huang, Xinyu Shi, Zecheng Hao +4
Spiking neural networks (SNNs) show great potential due to their energy efficiency, fast processing capabilities, and robustness. There are two main approaches to constructing SNNs…
Faster and Stronger: When ANN-SNN Conversion Meets Parallel Spiking Calculation
Zecheng Hao, Qichao Ma, Kang Chen +3
Spiking Neural Network (SNN), as a brain-inspired and energy-efficient network, is currently facing the pivotal challenge of exploring a suitable and efficient learning framework.…
USP-Gaussian: Unifying Spike-based Image Reconstruction, Pose Correction and Gaussian Splatting
Kang Chen, Jiyuan Zhang, Zecheng Hao +3
Spike cameras, as an innovative neuromorphic camera that captures scenes with the 0-1 bit stream at 40 kHz, are increasingly employed for the 3D reconstruction task via Neural Radi…
Rethinking SNN Online Training and Deployment: Gradient-Coherent Learning via Hybrid-Driven LIF Model
Zecheng Hao, Yifan Huang, Zijie Xu +4
Spiking Neural Networks (SNNs) are considered to have enormous potential in the future development of Artificial Intelligence due to their brain-inspired and energy-efficient prope…
Inner-Probe: Discovering Copyright-related Data Generation in LLM Architecture
Qichao Ma, Rui-Jie Zhu, Peiye Liu +8
Large Language Models (LLMs) utilize extensive knowledge databases and show powerful text generation ability. However, their reliance on high-quality copyrighted datasets raises co…
SpikeMM: Flexi-Magnification of High-Speed Micro-Motions
Baoyue Zhang, Yajing Zheng, Shiyan Chen +4
The amplification of high-speed micro-motions holds significant promise, with applications spanning fault detection in fast-paced industrial environments to refining precision in m…
Robust Stable Spiking Neural Networks
Jianhao Ding, Zhiyu Pan, Yujia Liu +2
Spiking neural networks (SNNs) are gaining popularity in deep learning due to their low energy budget on neuromorphic hardware. However, they still face challenges in lacking suffi…
Enhancing Adversarial Robustness in SNNs with Sparse Gradients
Yujia Liu, Tong Bu, Jianhao Ding +3
Spiking Neural Networks (SNNs) have attracted great attention for their energy-efficient operations and biologically inspired structures, offering potential advantages over Artific…
Implementing feature binding through dendritic networks of a single neuron
Yuanhong Tang, Shanshan Jia, Tiejun Huang +2
A single neuron receives an extensive array of synaptic inputs through its dendrites, raising the fundamental question of how these inputs undergo integration and summation, culmin…
SpikeReveal: Unlocking Temporal Sequences from Real Blurry Inputs with Spike Streams
Kang Chen, Shiyan Chen, Jiyuan Zhang +4
Reconstructing a sequence of sharp images from the blurry input is crucial for enhancing our insights into the captured scene and poses a significant challenge due to the limited t…
LM-HT SNN: Enhancing the Performance of SNN to ANN Counterpart through Learnable Multi-hierarchical Threshold Model
Zecheng Hao, Xinyu Shi, Yujia Liu +2
Compared to traditional Artificial Neural Network (ANN), Spiking Neural Network (SNN) has garnered widespread academic interest for its intrinsic ability to transmit information in…
Unsupervised Optical Flow Estimation with Dynamic Timing Representation for Spike Camera
Lujie Xia, Ziluo Ding, Rui Zhao +5
Efficiently selecting an appropriate spike stream data length to extract precise information is the key to the spike vision tasks. To address this issue, we propose a dynamic timin…
Unveiling the Potential of Spike Streams for Foreground Occlusion Removal from Densely Continuous Views
Jiyuan Zhang, Shiyan Chen, Yajing Zheng +2
The extraction of a clean background image by removing foreground occlusion holds immense practical significance, but it also presents several challenges. Presently, the majority o…
Spike timing reshapes robustness against attacks in spiking neural networks
Jianhao Ding, Zhaofei Yu, Tiejun Huang +1
The success of deep learning in the past decade is partially shrouded in the shadow of adversarial attacks. In contrast, the brain is far more robust at complex cognitive tasks. Ut…
Spike Stream Denoising via Spike Camera Simulation
Liwen hu, Lei Ma, Zhaofei Yu +2
As a neuromorphic sensor with high temporal resolution, the spike camera shows enormous potential in high-speed visual tasks. However, the high-speed sampling of light propagation…
Optimal ANN-SNN Conversion for High-accuracy and Ultra-low-latency Spiking Neural Networks
Tong Bu, Wei Fang, Jianhao Ding +3
Spiking Neural Networks (SNNs) have gained great attraction due to their distinctive properties of low power consumption and fast inference on neuromorphic hardware. As the most ef…
Exploring Efficient Asymmetric Blind-Spots for Self-Supervised Denoising in Real-World Scenarios
Shiyan Chen, Jiyuan Zhang, Zhaofei Yu +1
Self-supervised denoising has attracted widespread attention due to its ability to train without clean images. However, noise in real-world scenarios is often spatially correlated,…
SpikeCV: Open a Continuous Computer Vision Era
Yajing Zheng, Jiyuan Zhang, Rui Zhao +5
SpikeCV is a new open-source computer vision platform for the spike camera, which is a neuromorphic visual sensor that has developed rapidly in recent years. In the spike camera, e…
Bridging the Gap between ANNs and SNNs by Calibrating Offset Spikes
Zecheng Hao, Jianhao Ding, Tong Bu +2
Spiking Neural Networks (SNNs) have attracted great attention due to their distinctive characteristics of low power consumption and temporal information processing. ANN-SNN convers…
Reducing ANN-SNN Conversion Error through Residual Membrane Potential
Zecheng Hao, Tong Bu, Jianhao Ding +2
Spiking Neural Networks (SNNs) have received extensive academic attention due to the unique properties of low power consumption and high-speed computing on neuromorphic chips. Amon…
GraphReg: Dynamical Point Cloud Registration with Geometry-aware Graph Signal Processing
Zhao Mingyang, Ma Lei, Jia Xiaohong +2
This study presents a high-accuracy, efficient, and physically induced method for 3D point cloud registration, which is the core of many important 3D vision problems. In contrast t…