Google Inc.

Navin Sarma

Janne Matias Kontkanen

Dominik Philemon Kaeser

David Salesin

Brian Curless

Jamie Aspinall

Jonathan Tilton Barron

Paul E Debevec

Sofien Bouaziz

Sean Ryan Francesco Fanello

Christoph Rhemann

Rohit Kumar Pandey

Yael Pritch Knaan

Yun-Ta Tsai

Chloe LeGendre

Huizhong Chen

Orly Liba

David Edward Jacobs

Alexander Schiffhauer

Longqi Cai

Bryan Feldman

Siyang Li

Michael Milne

A media application receives user input that indicates one or more objects to be erased from a media item. The media application translates the user input to a bounding box. The media application provides a crop of the media item based on the bounding box to a segmentation machine-learning model. The segmentation machine-learning model outputs a segmentation mask for one or more segmented objects in the crop of the media item and a corresponding segmentation score that indicates a quality of the segmentation mask.

Performing segmentation of objects in media items based on user input

Apparatus and methods related to applying lighting models to images of objects are provided. An example method includes applying a geometry model to an input image to determine a surface orientation map indicative of a distribution of lighting on an object based on a surface geometry. The method further includes applying an environmental light estimation model to the input image to determine a direction of synthetic lighting to be applied to the input image. The method also includes applying, based on the surface orientation map and the direction of synthetic lighting, a light energy model to determine a quotient image indicative of an amount of light energy to be applied to each pixel of the input image. The method additionally includes enhancing, based on the quotient image, a portion of the input image. One or more neural networks can be trained to perform one or more of the aforementioned aspects.

Enhanced photo relighting based on machine learning models

A media application selects, from a collection of images associated with a user account, candidate pairs of images, where each pair includes a first static image and a second static image from the user account. The media application applies a filter to select a particular pair of images from the candidate pairs of images. The media application generates, using an image interpolator, one or more intermediate images based on the particular pair of images. The media application generates a video that includes three or more frames arranged in a sequence, where a first frame of the sequence is the first static image, a last frame of the sequence is the second static image, and each of the one or more intermediate images is a corresponding intermediate frame of the sequence between the first frame and the last frame.

Using interpolation to generate a video from static images

Growing community of inventors

Palo Alto, CA, United States of America

Navin Sarma