3 citations · 6 across the 7 of their papers we have counts for
7 papers
SphereVideo: Prototype-anchored Hyperspherical Boundary for Continual AI-generated Video Detection
Fei Li, Yue Yu, Yuran Wang +3
AI-generated video (AIGV) detection aims to distinguish real videos from AI-generated ones. In practice, detectors trained on existing data often fail to generalize to newly emergi…
Uncertainty-Aware Token Importance Estimation in Spiking Transformers
Wenxuan Liu, Zecheng Hao, Tong Bu +2
Spiking transformers have shown strong potential for neuromorphic vision, yet their token processing across multiple spiking steps still introduces substantial redundancy and infer…
SPAN: Continuous Modeling of Suspicion Progression for Temporal Intention Localization
Xinyi Hu, Yuran Wang, Ruixu Zhang +3
Temporal Intention Localization (TIL) is crucial for video surveillance, focusing on identifying varying levels of suspicious intentions to improve security monitoring. However, ex…
Beyond the Individual: Introducing Group Intention Forecasting with SHOT Dataset
Ruixu Zhang, Yuran Wang, Xinyi Hu +5
Intention recognition has traditionally focused on individual intentions, overlooking the complexities of collective intentions in group settings. To address this limitation, we in…
Anomize: Better Open Vocabulary Video Anomaly Detection
Fei Li, Wenxuan Liu, Jingjing Chen +4
Open Vocabulary Video Anomaly Detection (OVVAD) seeks to detect and classify both base and novel anomalies. However, existing methods face two specific challenges related to novel…
Devil is in Details: Locality-Aware 3D Abdominal CT Volume Generation for Self-Supervised Organ Segmentation
Yuran Wang, Zhijing Wan, Yansheng Qiu +1
In the realm of medical image analysis, self-supervised learning (SSL) techniques have emerged to alleviate labeling demands, while still facing the challenge of training data scar…
Contributing Dimension Structure of Deep Feature for Coreset Selection
Zhijing Wan, Zhixiang Wang, Yuran Wang +3
Coreset selection seeks to choose a subset of crucial training samples for efficient learning. It has gained traction in deep learning, particularly with the surge in training data…