公开(公告)号：US20210312635A1

公开(公告)日：2021-10-07

申请号：US16839209

申请日：2020-04-03

Applicant: ADOBE INC.

Inventor： Brian Lynn PRICE ,  Scott David COHEN ,  Henghui DING

IPC: G06T7/143 ,  G06K9/46 ,  G06K9/62 ,  G06N7/00 ,  G06N3/08

Abstract: Methods and systems are provided for optimal segmentation of an image based on multiple segmentations. In particular, multiple segmentation methods can be combined by taking into account previous segmentations. For instance, an optimal segmentation can be generated by iteratively integrating a previous segmentation (e.g., using an image segmentation method) with a current segmentation (e.g., using the same or different image segmentation method). To allow for optimal segmentation of an image based on multiple segmentations, one or more neural networks can be used. For instance, a convolutional RNN can be used to maintain information related to one or more previous segmentations when transitioning from one segmentation method to the next. The convolutional RNN can combine the previous segmentation(s) with the current segmentation without requiring any information about the image segmentation method(s) used to generate the segmentations.

公开(公告)号：US20210158139A1

公开(公告)日：2021-05-27

申请号：US16691110

申请日：2019-11-21

Applicant: ADOBE INC.

Inventor： Long MAI ,  Yannick HOLD-GEOFFROY ,  Naoto INOUE ,  Daichi ITO ,  Brian Lynn PRICE

IPC: G06N3/08 ,  G06T15/80 ,  G06T15/50 ,  G06T5/50

Abstract: Embodiments of the present invention provide systems, methods, and non-transitory computer storage media for generating an ambient occlusion (AO) map for a 2D image that can be combined with the 2D image to adjust the contrast of the 2D image based on the geometric information in the 2D image. In embodiments, using a trained neural network, an AO map for a 2D image is automatically generated without any predefined 3D scene information. Optimizing the neural network to generate an estimated AO map for a 2D image requires training, testing, and validating the neural network using a synthetic dataset comprised of pairs of images and ground truth AO maps rendered from 3D scenes. By using an estimated AO map to adjust the contrast of a 2D image, the contrast of the image can be adjusted to make the image appear lifelike by modifying the shadows and shading in the image based on the ambient lighting present in the image.