VRT is a transformer-based architecture for video restoration tasks including super-resolution, deblurring, and denoising. It is implemented in PyTorch and provides pretrained models achieving state-of-the-art performance on benchmarks like REDS, Vimeo90K, and Vid4. The model processes video frames using attention mechanisms to leverage temporal information for high-quality video enhancement.