Generalized video anomaly event detection: Systematic taxonomy and comparison of deep models
Video Anomaly Detection (VAD) serves as a pivotal technology in the intelligent surveillance
systems, enabling the temporal or spatial identification of anomalous events within videos …
systems, enabling the temporal or spatial identification of anomalous events within videos …
Learning prompt-enhanced context features for weakly-supervised video anomaly detection
Weakly supervised video anomaly detection aims to locate abnormal activities in untrimmed
videos without the need for frame-level supervision. Prior work has utilized graph …
videos without the need for frame-level supervision. Prior work has utilized graph …
Improving generalization in visual reinforcement learning via conflict-aware gradient agreement augmentation
Learning a policy with great generalization to unseen environments remains challenging but
critical in visual reinforcement learning. Despite the success of augmentation combination in …
critical in visual reinforcement learning. Despite the success of augmentation combination in …
Robust emotion recognition in context debiasing
Context-aware emotion recognition (CAER) has recently boosted the practical applications
of affective computing techniques in unconstrained environments. Mainstream CAER …
of affective computing techniques in unconstrained environments. Mainstream CAER …
What2comm: Towards communication-efficient collaborative perception via feature decoupling
Multi-agent collaborative perception has received increasing attention recently as an
emerging application in driving scenarios. Despite advancements in previous approaches …
emerging application in driving scenarios. Despite advancements in previous approaches …
Deep learning for video anomaly detection: A review
Video anomaly detection (VAD) aims to discover behaviors or events deviating from the
normality in videos. As a long-standing task in the field of computer vision, VAD has …
normality in videos. As a long-standing task in the field of computer vision, VAD has …
Stochastic video normality network for abnormal event detection in surveillance videos
Abstract Video Anomaly Detection (VAD) aims to automatically identify unexpected spatial–
temporal patterns to detect abnormal events in surveillance videos. Existing unsupervised …
temporal patterns to detect abnormal events in surveillance videos. Existing unsupervised …
Learning causality-inspired representation consistency for video anomaly detection
Video anomaly detection is an essential yet challenging task in the multimedia community,
with promising applications in smart cities and secure communities. Existing methods …
with promising applications in smart cities and secure communities. Existing methods …
Efficient decision-based black-box patch attacks on video recognition
Abstract Although Deep Neural Networks (DNNs) have demonstrated excellent
performance, they are vulnerable to adversarial patches that introduce perceptible and …
performance, they are vulnerable to adversarial patches that introduce perceptible and …
Freq-hd: An interpretable frequency-based high-dynamics affective clip selection method for in-the-wild facial expression recognition in videos
The in-the-wild dynamic facial expression recognition (DFER) has been challenging due to
several high-dynamics factors such as limited dynamic expression-related frames and …
several high-dynamics factors such as limited dynamic expression-related frames and …