1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CR2024★ 1 cited
Attacking Transformers with Feature Diversity Adversarial Perturbation
Chenxing Gao, Hang Zhou, Junqing Yu +4
Understanding the mechanisms behind Vision Transformer (ViT), particularly its vulnerability to adversarial perturba tions, is crucial for addressing challenges in its real-world a…
cs.CV2023
Multi-level Memory-augmented Appearance-Motion Correspondence Framework for Video Anomaly Detection
Xiangyu Huang, Caidan Zhao, Jinghui Yu +2
Frame prediction based on AutoEncoder plays a significant role in unsupervised video anomaly detection. Ideally, the models trained on the normal data could generate larger predict…
cs.CV2023★ 1 cited
Synthetic Pseudo Anomalies for Unsupervised Video Anomaly Detection: A Simple yet Efficient Framework based on Masked Autoencoder
Xiangyu Huang, Caidan Zhao, Chenxing Gao +2
Due to the limited availability of anomalous samples for training, video anomaly detection is commonly viewed as a one-class classification problem. Many prevalent methods investig…