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A deep learning project to predict and generate future video frames using models like ConvLSTM, PredRNN, and Transformers, leveraging the UCF101 dataset. The repository includes preprocessing, model training, video generation, an interactive UI, and evaluation metrics to compare model performance in video synthesis and temporal prediction tasks.
🎯 Production-ready implementation of video prediction models using PyTorch. Features Enhanced ConvLSTM with temporal attention, PredRNN with spatiotemporal memory, and Transformer-based architecture.