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Found 5 papers, 1 papers with code
Ano-Graph: Learning Normal Scene Contextual Graphs to Detect Video Anomalies
Video anomaly detection has proved to be a challenging task owing to its unsupervised training procedure and high spatio-temporal complexity existing in real-world scenarios.
G2D: Generate to Detect Anomaly
Previous researches solve this problem as a One-Class Classification (OCC) task where they train a reference model on all of the available samples.
Deep-HR: Fast Heart Rate Estimation from Face Video Under Realistic Conditions
In this paper, we propose a simple yet efficient approach to benefit the advantages of the Deep Neural Network (DNN) by simplifying HR estimation from a complex task to learning from very correlated representation to HR.
AVID: Adversarial Visual Irregularity Detection
Real-time detection of irregularities in visual data is very invaluable and useful in many prospective applications including surveillance, patient monitoring systems, etc.
A Novel Approach For Finger Vein Verification Based on Self-Taught Learning
In this paper, we propose a method for user Finger Vein Authentication (FVA) as a biometric system.
