9 citations · 11 across the 6 of their papers we have counts for
6 papers
Robust Deepfake Detection, NTIRE 2026 Challenge: Report
Benedikt Hopf, Radu Timofte, Chenfan Qu +54
Robustness is a long-overlooked problem in deepfake detection. However, detection performance is nearly worthless in the real world if it suffers under exposure to even slight imag…
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…
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…
Updated version: A Video Anomaly Detection Framework based on Appearance-Motion Semantics Representation Consistency
Xiangyu Huang, Caidan Zhao, Zhiqiang Wu
Video anomaly detection is an essential but challenging task. The prevalent methods mainly investigate the reconstruction difference between normal and abnormal patterns but ignore…
Rate-Perception Optimized Preprocessing for Video Coding
Chengqian Ma, Zhiqiang Wu, Chunlei Cai +5
In the past decades, lots of progress have been done in the video compression field including traditional video codec and learning-based video codec. However, few studies focus on…
A Video Anomaly Detection Framework based on Appearance-Motion Semantics Representation Consistency
Xiangyu Huang, Caidan Zhao, Yilin Wang +1
Video anomaly detection refers to the identification of events that deviate from the expected behavior. Due to the lack of anomalous samples in training, video anomaly detection be…