Self-Supervised Feature Learning by Learning to Spot Artifacts. In CVPR, 2018.
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Updated
Mar 24, 2023 - Python
Self-Supervised Feature Learning by Learning to Spot Artifacts. In CVPR, 2018.
Official PyTorch Implementation of Guarding Barlow Twins Against Overfitting with Mixed Samples
Coursework solutions for a 3rd year Computer Science module on Deep Learning @ Durham University. Uses a conditional WGAN-GP implementation to generate images from the CIFAR-10 and STL-10 datasets.
3rd Year: 1st - 104/100. Generative Modelling: Applying GANs to generate out-of-sample inter-class images - "The Mythical Pegasus: A Mysterious Journey".
DC-AE (Deep Compression Autoencoder)
Implementation of the algorithm Contrastive Multiview Coding (CMC) combined with Momentum Contrast (MoCo) for self-supervised learning of images.
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