Sony Group Corporation

Sony Corporation

Gary Lyons

Jong Hwa Lee

Edward Theodore Winter

Seunghan Kim

Sean Kennedy

Fredrik Carpio

Praggya Garg

Luis Vasconcelos

Moises Tafolla

Allison Langley

Alexander Stoneham

Kenji Suzuki

Nikolaos Georgis

David Andrew Young

Paul Jin Hwang

Priyan Gunatilake

Adrian Crisan

Eric Hsiao

Sriram Sampathkumaran

Brent Faust

Jenny Fredriksson

Kevin Barnes

Michael Nientse Chang

Andrew Lee Lawton

Rommel Garay

David Young

An electronic device receives a set of 2D images comprising at least first 2D image of an object of interest and detects a plurality of 2D landmarks on the first 2D image. The detected plurality of 2D landmarks corresponds to shape-features of the object of interest. The electronic device aligns a first three-dimensional (3D) shape model of a reference object by fitting 2D landmarks of the first 3D shape model to the detected plurality of 2D landmarks. The electronic device estimates texture mapping information between the object of interest and the aligned first 3D shape model and generates a dataset by including the first 2D image, the aligned first 3D shape model, and the estimated texture mapping information as a first sample of the dataset. Based on the generated dataset, the electronic device trains a neural network model on a task of 3D reconstruction from a single 2D image.

3D dataset generation for neural network model training

An electronic device and method of dataset cleaning is provided. The electronic device receives a dataset comprising a plurality of samples, of which a first sample comprises a 2D image of an object of interest and a 3D shape model of the object of interest. The electronic device determines 2D landmarks from the 2D image and extracts 3D landmarks from the 3D shape model. The electronic device computes an error between the determined 2D landmarks and corresponding 2D locations of the extracted 3D landmarks on the 2D image, based on an error metric. Thereafter, the electronic device determines the computed error to be above a threshold. Based on the determination that the computed error is above the threshold, the electronic device updates the dataset by a removal of the first sample from the dataset and trains a neural network on a task of 3D reconstruction, based on the updated dataset.

Cleaning dataset for neural network training

A system and method for node-based image colorization is provided. The system receives a first user input via a Graphical User Interface (GUI) of an image/video editing application and controls a display device to display a node graph on the GUI based on the first user input. The node graph includes an input node to select grayscale images and a colorization node which may represent a workflow for colorization of at least a first object in the grayscale images. The system receives a second user input associated with a setting of the colorization node and selects an image colorization model based on the second user input. The system executes the workflow associated with the colorization node to transmit the grayscale images to a computing device that hosts the selected image colorization model, and to receive colorized images including at least the first object colorized based on a color effect.

Node-based image colorization on image/video editing applications

An electronic device for programmable rig control for three-dimensional (3D) reconstruction is provided. The electronic device controls a first image sensor to capture a first image of a first scene which includes a set of subjects. The electronic device further feed a first input to a neural network. The electronic device further receives a first output from the neural network based on the fed first input. The electronic device further selects one or more image sensors based on the received first output. The electronic device further controls a first set of structures associated with the selected one or more image sensors to re-arrange a rig around a three-dimensional (3D) physical space. The electronic device further controls a first set of image sensors, in the re-arranged rig, to capture one or more images for generation of one or more three-dimensional (3D) models of a first subject in the 3D physical space.

Programmable rig control for three-dimensional (3D) reconstruction

A computing system and method for neural network-based image colorization is provided. The computing system obtains a reference color image by selective application of a color effect on a region of interest of an input image and controls a display device to display a first node graph on a Graphical User Interface of an image/video editing application. The first node graph includes a colorization node representing a first workflow for colorization of at least a first object in grayscale images of a first image feed. The computing system selects the reference color image based on a user input and executes the first workflow associated with the colorization node by feeding the reference color image and the first image feed as an input to a neural network-based colorization model. The computing system receives a second image feed comprising colorized images as output of the neural network-based colorization model for the input.

Neural network-based image colorization on image/video editing applications

Implementations generally provide a user interface for video annotation tools. In some implementations, a method includes obtaining at least one video of at least one object performing at least one action displaying one or more portions of the at least one video in a user interface. The method further includes displaying a plurality of annotation tracks in the user interface, where each annotation track of the plurality of annotation tracks is associated with one or more of the at least one object and the at least one action in the at least one video. The method further includes obtaining one or more annotations associated with the at least one video based on the plurality of annotation tracks.

Providing a user interface for video annotation tools

Various aspects of a method and system to present information via a user interface are disclosed herein. In accordance with an embodiment, the method includes detection of an orientation of an electronic device. The electronic device overlays one or more layers of information on the user interface displayed at the electronic device. Transparency of the overlaid one or more layers of information is dynamically adjusted based on the detected orientation of the electronic device.

Method and system for presenting information via a user interface

A computer establishes a wireless wide area network (WWAN) account simply by entering his telephone number in a user interface (UI) which is sent to an Internet server and correlated with the user's telephone account. A utility notes when a usage limitation for a period is approaching and in response disables wireless updates and automatically executes the updates when a landline connection is sensed.

Simplified activation and management of wireless wide area network (WWAN) account

A method of managing content related to a plurality of social networking websites. The method comprises accessing a first account that stores user's authentication information of the plurality of the networking websites and connecting to the plurality of social networking websites. Content associated with a second account is obtained from each of the plurality of social networking websites and service capabilities of each of the plurality of social networking websites are tracked. The obtained content from all the social networking websites is displayed on a single page and service information applicable to content is provided.

Method and system for content distribution management

A user of a user computer whose hard disk drive (HDD) is 'fried' can press a special key to cause BIOS to automatically gather location information about the computer from its GPS receiver and gather information about the HDD, activate a WWAN transceiver, and automatically send the location and HDD information over the WWAN to a service computer, which may return a location of a nearest service center to the user computer and any other advice including recovery advice for the HDD that the service center might be able to divine from the information sent to it by the user computer.

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San Diego, CA, United States of America

Gary Lyons