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公开(公告)号：US20230101704A1
公开(公告)日：2023-03-30
申请号：US17898704
申请日：2022-08-30
Inventor： Ruifeng DENG , Tianwei LIN , Fu LI
Abstract: The present disclosure discloses a video generation method and apparatus, an electronic device and a readable storage medium, and relates to the field of artificial intelligence, and in particular, to computer vision and deep learning technologies, which may specifically be used in 3D visual scenarios. A specific implementation scheme involves: determining a reference portrait in an original image; performing posture change processing on the reference portrait in the original image by using a nonlinear function, to obtain at least one change image; and generating a dynamic video of the reference portrait according to the original image and the at least one change image.
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2.发明申请公开(公告)号：US20220327757A1
公开(公告)日：2022-10-13
申请号：US17849225
申请日：2022-06-24
Inventor： Ruifeng DENG , Tianwei LIN , Fu LI
Abstract: An apparatus, an electronic device, and a storage medium may implement a method for generating a dynamic video of a character. The method includes: identifying a character contour area from a first picture containing a character image; acquiring a plurality of sampling points in the first picture based on the character contour area, and dividing the first picture into a plurality of triangles by each of the sampling points; deforming at least a portion of the plurality of triangles in the first picture to obtain a second picture; and acquiring at least one intermediate picture between the first picture and the second picture, and generating the dynamic video of the character comprising the first picture, the second picture and the at least one intermediate picture.
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公开(公告)号：US20220027661A1
公开(公告)日：2022-01-27
申请号：US17479872
申请日：2021-09-20
Inventor： Ruifeng DENG , Tianwei LIN , Xin LI , Fu LI
Abstract: There is provided a method and an apparatus of processing image, an electronic device, and a storage medium, which relates to a field of artificial intelligence technology, and specifically relates to a computer vision and deep learning technology applied to an image acquisition scene. The method includes performing a saliency detection on an original image to obtain a saliency map of the original image; performing a semantic segmentation on the original image to obtain a semantic segmentation map of the original image; modifying the saliency map by using the semantic segmentation map, so as to obtain a target map containing a target object; and cropping the original image based on a position of the target object in the target map.
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