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Found 5 papers, 4 papers with code
Harnessing Large Language Models for Training-free Video Anomaly Detection
Video anomaly detection (VAD) aims to temporally locate abnormal events in a video.
Delving into CLIP latent space for Video Anomaly Recognition
We tackle the complex problem of detecting and recognising anomalies in surveillance videos at the frame level, utilising only video-level supervision.
Audio-Visual Dataset and Method for Anomaly Detection in Traffic Videos
We introduce the first audio-visual dataset for traffic anomaly detection taken from real-world scenes, called MAVAD, with a diverse range of weather and illumination conditions.
ConfMix: Unsupervised Domain Adaptation for Object Detection via Confidence-based Mixing
Unsupervised Domain Adaptation (UDA) for object detection aims to adapt a model trained on a source domain to detect instances from a new target domain for which annotations are not available.
Graph-based Generative Face Anonymisation with Pose Preservation
With the goal to maintain the geometric attributes of the source face, i. e., the facial pose and expression, and to promote more natural face generation, we propose to exploit a Bipartite Graph to explicitly model the relations between the facial landmarks of the source identity and the ones of the condition identity through a deep model.
