Google Inc.

Deepmind Technologies Limited

Christopher Sigurd Fougner

Norman Casagrande

Christopher Gamble

Benjamin Hal Murdoch

Peeyush Agarwal

Thomas Degris

Nishant P Patil

Chenjie Gu

Ching Yin Derek Pang

Cheng Chen

Rene Andre Claus

Ching-Han Chiang

Hongzi Mao

Marisabel Guevara Hechtman

Daniel James Visentin

Charles Booth Schaff

Alejandro Ramirez Bellido

Jingning Han

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for encoding video comprising a sequence of video frames. In one aspect, a method comprises for one or more of the video frames: obtaining a feature embedding for the video frame; processing the feature embedding using a rate control machine learning model to generate a respective score for each of multiple quantization parameter values; selecting a quantization parameter value using the scores; determining a cumulative amount of data required to represent: (i) an encoded representation of the video frame and (ii) encoded representations of each preceding video frame; determining, based on the cumulative amount of data, that a feedback control criterion for the video frame is satisfied; updating the selected quantization parameter value; and processing the video frame using an encoding model to generate the encoded representation of the video frame.

Rate control machine learning models with feedback control for video encoding

A computer-implemented method for adaptive display brightness adjustment, the method comprising: obtaining current state data characterizing a current state of a device having a display with an adjustable brightness; providing the current state data as input to a brightness prediction machine learning model, wherein the model is configured to process the current state data in accordance with current values of a set of model parameters to generate as output a proposed display brightness for the display of the device; setting the brightness of the display to a brightness that is lower than the proposed display brightness in accordance with an exploration policy; determining whether a user of the device manually adjusts the display brightness; and in response to determining that the user did not manually adjust the display brightness, using the lower brightness as a target output for adjusting the current values of the set of model parameters.

Adaptive display brightness adjustment

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Küsnacht, Switzerland

Christopher Sigurd Fougner