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Human action classification system with pose-based (MediaPipe) and video-based (3D CNN) models. Features 100+ architectures for real-time pose classification and temporal models pretrained on UCF-101/HMDB51. Applications include autonomous vehicles, video surveillance, and action recognition research.
A deep learning-based video classification system for detecting shoplifting behavior in surveillance footage. The project includes both a custom CNN-LSTM architecture built from scratch and a fine-tuned pretrained R3D-18 (3D ResNet) model, along with a production-ready Django web application for deployment.