A lightweight deep learning framework combining 2D CNNs (ResNet50, EfficientNet, ViT), LSTM, and attention mechanisms to recognize fitness movements from video data. Evaluated on the UCF101 fitness subset, the model balances accuracy with computational efficiency and outperforms traditional 3D CNNs in resource-constrained environments.
