6 papers
Breaking the Modality Wall: Time-step Mixup for Efficient Spiking Knowledge Transfer from Static to Event Domain
Yuqi Xie, Shuhan Ye, Yi Yu +7
The integration of event cameras and spiking neural networks (SNNs) promises energy-efficient visual intelligence, yet scarce event data and the sparsity of DVS outputs hinder effe…
Time-step Mixup for Efficient Spiking Knowledge Transfer from Appearance to Event Domain
Yuqi Xie, Shuhan Ye, Yi Yu +7
The integration of event cameras and spiking neural networks holds great promise for energy-efficient visual processing. However, the limited availability of event data and the spa…
GV-VAD : Exploring Video Generation for Weakly-Supervised Video Anomaly Detection
Suhang Cai, Xiaohao Peng, Chong Wang +2
Video anomaly detection (VAD) plays a critical role in public safety applications such as intelligent surveillance. However, the rarity, unpredictability, and high annotation cost…
Cross Knowledge Distillation between Artificial and Spiking Neural Networks
Shuhan Ye, Yuanbin Qian, Chong Wang +4
Recently, Spiking Neural Networks (SNNs) have demonstrated rich potential in computer vision domain due to their high biological plausibility, event-driven characteristic and energ…
UCF-Crime-DVS: A Novel Event-Based Dataset for Video Anomaly Detection with Spiking Neural Networks
Yuanbin Qian, Shuhan Ye, Chong Wang +3
Video anomaly detection plays a significant role in intelligent surveillance systems. To enhance model's anomaly recognition ability, previous works have typically involved RGB, op…
Zero-Shot Hashing Based on Reconstruction With Part Alignment
Yan Jiang, Zhongmiao Qi, Jianhao Li +3
Hashing algorithms have been widely used in large-scale image retrieval tasks, especially for seen class data. Zero-shot hashing algorithms have been proposed to handle unseen clas…