US 12,217,169 B2
Local neural implicit functions with modulated periodic activations
Ishit bhadresh Mehta, San Diego, CA (US); Michaël Gharbi, San Francisco, CA (US); Connelly Barnes, Seattle, WA (US); and Elya Shechtman, Seattle, WA (US)
Assigned to ADOBE INC., San Jose, CA (US)
Filed by ADOBE INC., San Jose, CA (US)
Filed on Mar. 11, 2021, as Appl. No. 17/198,670.
Prior Publication US 2022/0292341 A1, Sep. 15, 2022
Int. Cl. G06N 3/04 (2023.01); G06N 3/0455 (2023.01); G06N 3/048 (2023.01); G06N 3/08 (2023.01); G06T 3/4007 (2024.01); G06T 5/77 (2024.01)
CPC G06N 3/08 (2013.01) [G06N 3/0455 (2023.01); G06N 3/048 (2023.01); G06T 3/4007 (2013.01); G06T 5/77 (2024.01); G06T 2207/10016 (2013.01)] 17 Claims
OG exemplary drawing
 
1. A method for signal processing, comprising:
receiving a digital signal comprising signal values corresponding to discrete sample locations;
generating modulation parameters based on the digital signal using a modulator network, wherein each of a plurality of modulator layers of the modulator network outputs a set of the modulation parameters; and
generating a predicted signal value of the digital signal at an additional location using a synthesizer network, computing, at a first synthesizer layer, a product of a set of modulation parameters output by a modulator layer and a continuous function of a first set of features to produce a second set of features, wherein the second set of features are input to a second synthesizer layer, wherein each of a plurality of synthesizer layers of the synthesizer network operates based on the set of the modulation parameters from a corresponding modulator layer of the modulator network.