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Found 3 papers, 1 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.
Unifying Synergies between Self-supervised Learning and Dynamic Computation
Computationally expensive training strategies make self-supervised learning (SSL) impractical for resource constrained industrial settings.
Efficient CNN Implementation for Eye-Gaze Estimation on Low-Power/Low-Quality Consumer Imaging Systems
Accurate and efficient eye gaze estimation is important for emerging consumer electronic systems such as driver monitoring systems and novel user interfaces.
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