Do you have two left feet? Do you avoid the dance floor out of fear of embarrassment? If you’ve ever secretly wished you could move your body like Joaquín Cortés — well, at least in a video — a new AI-powered 3D body mesh recovery module called Liquid Warping GAN can give you a leg up.
In the paper ChipGAN: A Generative Adversarial Network for Chinese Ink Wash Painting Style Transfer, a team of researchers from Peking University and Tsinghua University propose an end-to-end GAN-based architecture that can transfer input photos into the style of Chinese ink wash paintings.
A team of researchers have proposed a number of “recommendations to data providers, academic publishers, and the ML4H research community in order to promote reproducible research moving forward” in their new paper Reproducibility in Machine Learning for Health.
Researchers from Element AI, MILA (Montréal Institute for Learning Algorithms), and Université de Montréal have introduced a powerful transfer language model that can summarize long scientific articles effectively, outperforming traditional seq2seq approaches.
Now a group of researchers from the Seattle-based Allen Institute for Artificial Intelligence (AI2) have shown how trigger words and phrases can “inflict targeted errors” on natural language processing (NLP) model outputs, prompting them to generate racist and hostile content.
For an AI system to acquire knowledge the way humans generally do it would need to interact with its surroundings and extract information through its own attention and analysis choices. That’s the idea behind a new paper from Microsoft Research, Polytechnique Montreal, MILA and and the University of Montreal.
In collaboration with Partnership on AI, Microsoft, and academics from top universities, Facebook today announced the Deepfake Detection Challenge (DFDC) with the aim of finding innovative deepfake detection solutions to help the media industry spot videos that have been morphed by AI models.