Nvidia Corporation

Hongxu Yin

Jan Kautz

Anjul Patney

Pavlo Molchanov

Jose Manuel Alvarez Lopez

Yazhou Xing

Amrita Mazumdar

Akshay Chawla

One or more embodiments include receiving one or more frames of a live video captured by a video capturing device, wherein the one or more frames include a current frame that is most-recently captured, identifying a set of reference frames included in the one or more frames based on at least the current frame, wherein each frame in the set of reference frames has a different exposure level relative to the current frame, determining, using one or more neural networks, a set of missing details for one or more regions of the current frame based on the set of reference frames, generating an updated version of the current frame based on the set of details, and outputting the updated version of the current frame in real-time.

Hallucinating details for over-exposed pixels in videos using learned reference frame selection

Apparatuses, systems, and techniques to generate images of objects. In at least one embodiment, one or more neural networks are trained to identify one or more objects within one or more images, and the one or more neural networks are used to generate an image of one or more objects.

Neural network training method

Growing community of inventors

San Jose, CA, United States of America

Hongxu Yin