2 citations · 4 across the 19 of their papers we have counts for
9 papers · 1 filter
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…
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…
Towards Low-latency Event-based Visual Recognition with Hybrid Step-wise Distillation Spiking Neural Networks
Xian Zhong, Shengwang Hu, Wenxuan Liu +4
Spiking neural networks (SNNs) have garnered significant attention for their low power consumption and high biological interpretability. Their rich spatio-temporal information proc…
SpikeGS: 3D Gaussian Splatting from Spike Streams with High-Speed Camera Motion
Jiyuan Zhang, Kang Chen, Shiyan Chen +3
Novel View Synthesis plays a crucial role by generating new 2D renderings from multi-view images of 3D scenes. However, capturing high-speed scenes with conventional cameras often…
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…
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…