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Небесная энциклопедия

Космические корабли и станции, автоматические КА и методы их проектирования, бортовые комплексы управления, системы и средства жизнеобеспечения, особенности технологии производства ракетно-космических систем

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Мониторинг СМИ

Мониторинг СМИ и социальных сетей. Сканирование интернета, новостных сайтов, специализированных контентных площадок на базе мессенджеров. Гибкие настройки фильтров и первоначальных источников.

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Применить Всего найдено 3. Отображено 3.
02-11-2022 дата публикации

Techniques for enhancing skin renders using neural network projection for rendering completion

Номер: GB0002606252A
Автор: DEREK EDWARD BRADLEY [US], PRASHANTH CHANDRAN [US], PAULO FABIANO URNAU GOTARDO [US], JEREMY RIVIERE [US], SEBASTIAN VALENTIN WINBERG [US], GASPARD ZOSS [US]
Принадлежит:

Techniques are disclosed for generating photorealistic images of head portraits. A rendering application renders a set of images that include the skin of a face and corresponding masks indicating pixels associated with the skin in the images. An inpainting application performs a neural projection technique to optimize a set of parameters that, when input into a generator model, produces a set of projection images, each of which includes a head portrait in which (1) skin regions resemble the skin regions of the face in a corresponding rendered image and (2) non-skin regions match the non-skin regions in the other projection images when the rendered set of images are standalone images or transition smoothly between consecutive projection images in the case when the rendered set of images are frames of a video. The rendered images can then be blended with corresponding projection images to generate composite images that are photorealistic.

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Номер записи: 1
31-05-2023 дата публикации

Transformer-based shape models

Номер: GB0002613240A
Автор: DEREK EDWARD BRADLEY [US], PRASHANTH CHANDRAN [US], PAULO FABIANO URNAU GOTARDO [US], GASPARD ZOSS [US]
Принадлежит:

A technique for synthesizing a shape includes generating a first plurality of offset tokens based on a first shape code and a first plurality of position tokens, wherein the first shape code represents a variation of a canonical shape and wherein the first plurality of position tokens represent a first plurality of positions on the canonical shape. A first plurality of offsets tokens associated with the first plurality of positions on the canonical shape are then generated and a first plurality of offsets associated with said tokens are generated. The shape is then generated based on the first plurality of offsets and the first plurality of positions. An encoder neural network to may be used generate a second shape code based on a set of offset tokens associated with a training shape.

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Номер записи: 2
23-11-2022 дата публикации

Adaptive convolutions in neural networks

Номер: GB0002606785A
Автор: DEREK EDWARD BRADLEY [US], PAULO FABIANO URNAU GOTARDO [US], GASPARD ZOSS [US], PRASHANTH CHANDRAN [CH]
Принадлежит:

A technique for performing style transfer between a content sample and a style sample is disclosed. The technique includes applying one or more neural network layers to a first latent representation of the style sample to generate one or more convolutional kernels. The technique also includes generating convolutional output by convolving a second latent representation of the content sample with the one or more convolutional kernels. The technique further includes applying one or more decoder layers to the convolutional output to produce a style transfer result that comprises one or more content-based attributes of the content sample and one or more style-based attributes of the style sample.

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Номер записи: 3