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Found 4 papers, 2 papers with code
Video Anomaly Detection via Spatio-Temporal Pseudo-Anomaly Generation : A Unified Approach
Video Anomaly Detection (VAD) is an open-set recognition task, which is usually formulated as a one-class classification (OCC) problem, where training data is comprised of videos with normal instances while test data contains both normal and anomalous instances.
Motion Aware Self-Supervision for Generic Event Boundary Detection
In this work, we address this issue by revisiting a simple and effective self-supervised method and augment it with a differentiable motion feature learning module to tackle the spatial and temporal diversities in the GEBD task.
Dynamic Channel Selection in Self-Supervised Learning
Currently, convnets pre-trained with self-supervision have obtained comparable performance on downstream tasks in comparison to their supervised counterparts in computer vision.
Investigating Memorability of Dynamic Media
The Predicting Media Memorability task in MediaEval'20 has some challenging aspects compared to previous years.
