公开(公告)号：US20200151509A1

公开(公告)日：2020-05-14

申请号：US16188130

申请日：2018-11-12

Applicant: ADOBE INC.

Inventor： Kalyan K. Sunkavalli ,  Sunil Hadap ,  Jonathan Eisenmann ,  Jinsong Zhang ,  Emiliano Gambaretto

IPC: G06K9/62 ,  G06K9/46

Abstract: Methods and systems are provided for determining high-dynamic range lighting parameters for input low-dynamic range images. A neural network system can be trained to estimate lighting parameters for input images where the input images are synthetic and real low-dynamic range images. Such a neural network system can be trained using differences between a simple scene rendered using the estimated lighting parameters and the same simple scene rendered using known ground-truth lighting parameters. Such a neural network system can also be trained such that the synthetic and real low-dynamic range images are mapped in roughly the same distribution. Such a trained neural network system can be used to input a low-dynamic range image determine high-dynamic range lighting parameters.

公开(公告)号：US10607329B2

公开(公告)日：2020-03-31

申请号：US15457192

申请日：2017-03-13

Applicant: ADOBE INC.

Inventor： Kalyan K. Sunkavalli ,  Xiaohui Shen ,  Mehmet Ersin Yumer ,  Marc-André Gardner ,  Emiliano Gambaretto

IPC: G06K9/62 ,  G06T7/00 ,  G06N3/04 ,  G06N3/08 ,  G06N20/10

Abstract: Methods and systems are provided for using a single image of an indoor scene to estimate illumination of an environment that includes the portion captured in the image. A neural network system may be trained to estimate illumination by generating recovery light masks indicating a probability of each pixel within the larger environment being a light source. Additionally, low-frequency RGB images may be generated that indicating low-frequency information for the environment. The neural network system may be trained using training input images that are extracted from known panoramic images. Once trained, the neural network system infers plausible illumination information from a single image to realistically illumination images and objects being manipulated in graphics applications, such as with image compositing, modeling, and reconstruction.

公开(公告)号：US20190259216A1

公开(公告)日：2019-08-22

申请号：US15900864

申请日：2018-02-21

Applicant: Adobe Inc.

Inventor： Emiliano Gambaretto ,  Vladimir Kim ,  Qingnan Zhou ,  Mehmet Ersin Yumer

IPC: G06T19/20 ,  G06T17/20

Abstract: Certain embodiments involve refining local parameterizations that apply two-dimensional (“2D”) images to three-dimensional (“3D”) models. For instance, a particular parameterization-initialization process is select based on one or more features of a target mesh region. An initial local parameterization for a 2D image is generated from this parameterization-initialization process. A quality metric for the initial local parameterization is computed, and the local parameterization is modified to improve the quality metric. The 3D model is modified by applying image points from the 2D image to the target mesh region in accordance with the modified local parameterization.