This repository re-implements the Efficient Sub-Pixel Convolutional Neural Network paper by Shi et al. from Twitter VX. The network learns to upscale low-resolution images to higher resolution by using a novel sub-pixel convolution layer that reconstructs the output from feature maps at the final layer. Built with TensorFlow, it demonstrates the approach on image super-resolution tasks with example outputs showing progressive quality improvement over training epochs.