Google researchers have created a machine learning system that adds color to black & white videos, and can also choose which specific objects, people and pets receive the color treatment. The technology is based on what’s called a convolutional neural network, which is architecturally suited for object tracking and video stabilization. Meanwhile, Nvidia has debuted an algorithm that slows down video, without the jitters, after it’s been captured, by using a neural network to create “in between” frames required for smooth motion. Continue reading Google, Nvidia Train Neural Networks to Post-Process Video

Nvidia debuted a deep learning method that can edit or reconstruct an image that is missing pixels or has holes via a process called “image inpainting.” The model can handle holes of “any shape, size, location or distance from image borders,” and could be integrated in photo editing software to remove undesirable imagery and replace it with a realistic digital image – instantly and with great accuracy. Previous AI-based approaches focused on rectangular regions in the image’s center and required post processing. Continue reading Nvidia’s New AI Method Can Reconstruct an Image in Seconds

At Nvidia’s GPU Technology Conference, the company’s chief executive Jen-Hsun Haung introduced Project Holodeck, which aims to provide an experimental multi-user virtual environment with real-time photorealistic graphics and real-world physics. The new technology, which uses Epic’s Unreal Engine 4 and Nvidia’s GameWorks, VRWorks and DesignWorks, is targeted at design engineers and their collaborators. Nvidia’s Project Holodeck demo involved Koenigsegg Automotive, a Swedish company that makes exotic sports cars. Continue reading Nvidia’s Project Holodeck: Photoreal Graphics in Shared VR