7 papers
Unveiling the Unknown: Open Vocabulary Object Detection with Scene Graphs
Yi Chen, Yinghao Lu, Zhehao Li +4
Open-vocabulary object detection seeks to identify novel object categories that were not part of the training data. Many knowledge distillation-based approaches have shown promisin…
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…
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…