APPARATUS AND METHOD FOR SYNTHESIZING 2D IMAGE AND MEDIA USING INVERSE RENDERING WITH 3D SPATIALLY VARYING LIGHTING INFORMATION ESTIMATION

    公开(公告)号:US20250157131A1

    公开(公告)日:2025-05-15

    申请号:US18393078

    申请日:2023-12-21

    Abstract: The present disclosure relates to an apparatus for synthesizing a 2D image and media using a reverse rendering including 3D spatially varying lighting information estimation, and the apparatus includes a target view analysis unit configured to estimate a normal map and direct lighting using a plurality of 2D images, a material estimation unit configured to reflect the normal map and direct lighting estimated from the target view analysis unit and estimate material information, a 3D lighting estimation unit configured to reflect the direct lighting estimated from the target view analysis unit and the material information estimated from the material estimation unit and estimate 3D spatially varying lighting information, and an image generation unit configured to reflect the estimated shapes, materials, and 3D spatially varying lighting information, synthesize the 2D images with 3D objects, and generate a synthesized image.

    METHOD FOR AUTOMATIC FACIAL IMPRESSION TRANSFORMATION, RECORDING MEDIUM AND DEVICE FOR PERFORMING THE METHOD

    公开(公告)号:US20180268207A1

    公开(公告)日:2018-09-20

    申请号:US15985173

    申请日:2018-05-21

    Abstract: A method for automatic facial impression transformation includes extracting landmark points for elements of a target face whose facial impression is to be transformed as well as distance vectors respectively representing distances of the landmark points, comparing the distance vectors to select a learning data set similar to the target face from a database, extracting landmark points and distance vectors from the learning data set, transforming a local feature of the target face based on the landmark points of the learning data set and score data for a facial impression, and transforming a global feature of the target face based on the distance vectors of the learning data set and the score data for the facial impression. Accordingly, a facial impression may be transformed in various ways while keeping an identity of a corresponding person.

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