Many recent successes in computer vision have been powered by the extension of BERTology beyond the mode of text-based data to image & video. Without a doubt, efficient Transformers which patchify input images a la ViT have initiated much of this progress. But in this post, we are interested in pretraining with self-supervised learning to develop compact representations we might use in various downstream tasks.
Datasets of real world interest often exhibit structures which are not exploited in research on benchmark datasets....
Blob Pitt's next big blockbuster We consider generative models among the most exciting applications of machine learning. This tech has reached a remarkable capacity to synthesize original multimedia content after learning a data distribution.
In this arena, the state-of-the-art has been dominated by a family of models called generative adversarial networks or GANs.
However, GANs are challenged by training instabilities. The latest StyleGAN2-ada mitigates mode collapse arising from overfit discriminators using test time data augmentation....
In our last post, we trained StyleGAN2 over a corpus of hundreds of thousands theatrical posters we scraped from sites like IMDb.
Then we explored image retrieval applications of StyleGAN2 after extracting embeddings by projecting our image corpus onto the learned latent factor space.
Image retrieval techniques can form the basis of personalized image recommendations as we use content similarity to generate new recommendations.
Netflix engineers posted about testing the impact on user engagement from artwork produced by their content creation team....
GANs consistently achieve state of the art performance in image generation by learning the distribution of an image corpus.
The newest models often use explicit mechanisms to learn factored representations for images which can be help provide faceted image retrieval, capable of conditioning output on key attributes.
In this post, we explore applying StyleGAN2 embeddings in image retrieval tasks.
StyleGAN2 To begin, we train a StyleGAN2 model to generate theatrical posters from our image corpus....
In a matter of months, the COVID-19 pandemic has besieged humanity and now the world wrestles to manage the population health challenges of a novel coronavirus with remarkable infectivity.
Organizing an effective response to blunt the impact of such a large, complex challenge demands a principled and scientific approach.
Better Planning by Forecasting Infections Reliable forecasting is crucial for planning and allocating limited resources efficiently and minimizing casualties....