Nvidia Corporation

Pranit P Kothari

Siddhant Pardeshi

Vinayak Vilas Gaikwad

Travis Muhlestein

Aditya Karra

Apparatuses, systems, and techniques are presented to generate image or video content. In at least one embodiment, one or more neural networks are used to generate one or more time-lapsed images of a second object based, at least in part, on one or more images of a first object.

Image generation using one or more neural networks

Apparatuses, systems, and techniques are presented to generate image or video content representing at least one point of view. In at least one embodiment, one or more neural networks are used to generate one or more images of one or more objects from a first point of view based at least in part upon one or more images of the one or more objects from a second point of view.

View generation using one or more neural networks

Apparatuses, systems, and techniques are presented to generate one or more interfaces. In at least one embodiment, one or more neural networks are used to generate one or more second graphical user interfaces based, at least in part, on one or more functional features of one or more first graphical user interfaces.

Interface translation using one or more neural networks

Apparatuses, systems, and techniques to facilitate understanding of media content using neural networks to adjust playback speed and volume based on environmental and other factors. In at least one embodiment, playback of media content is slowed down or sped up if audio associated with said media content is difficult to understand based on background noise, accent, difficulty of material, as well as other factors that decrease understandability of media content.

Media engagement through deep learning

Apparatuses, systems, and techniques are presented for generating instructional text. In at least one embodiment, an instructional video is analyzed to determine logical steps of a process or task demonstrated in that video, and instructive text is generated for those logical steps.

Instruction generation using one or more neural networks

Apparatuses, systems, and techniques are presented to generate panoramas from individual images. In at least one embodiment, one or more generative neural networks are used to generate a spherical panoramic image using features extracted from a single input image.

Panorama generation using one or more neural networks

Apparatuses, systems, and techniques to classify content. In at least one embodiment, a mixture of neural networks each trained to generate labels for various types of input are used to automatically generate appropriate content labels given an input.

Growing community of inventors

Pune, India

Pranit P Kothari