From the 1 of 6 linked papers with an AI index.
6 papers
ENCORE: Event-Assisted Complementary Motion Refinement for Learned Video Compression
Shuhan Ye, Hongbin Yu, Chenqi Kong +4
The paper introduces ENCORE, a framework that uses asynchronous event‑camera data to refine motion estimation in learned video compression, improving quality especially under chall…
Fire on Motion: Optimizing Video Pass-bands for Efficient Spiking Action Recognition
Shuhan Ye, Yuanbin Qian, Yi Yu +5
Spiking neural networks (SNNs) have gained traction in vision due to their energy efficiency, bio-plausibility, and inherent temporal processing. Yet, despite this temporal capacit…
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…
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…
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…