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11.发明申请Automatically Selecting Example Stylized Images for Image Stylization Operations Based on Semantic Content 有权自动选择基于语义内容的图像样式化操作的示例风格化图像公开(公告)号：US20160364625A1
公开(公告)日：2016-12-15
申请号：US14735822
申请日：2015-06-10
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Xiaohui Shen , Kalyan Sunkavalli , Joon-Young Lee
CPC classification number: G06T7/60 , G06K9/00624 , G06T7/90 , G06T11/001
Abstract: Systems and methods are provided for content-based selection of style examples used in image stylization operations. For example, training images can be used to identify example stylized images that will generate high-quality stylized images when stylizing input images having certain types of semantic content. In one example, a processing device determines which example stylized images are more suitable for use with certain types of semantic content represented by training images. In response to receiving or otherwise accessing an input image, the processing device analyzes the semantic content of the input image, matches the input image to at least one training image with similar semantic content, and selects at least one example stylized image that has been previously matched to one or more training images having that type of semantic content. The processing device modifies color or contrast information for the input image using the selected example stylized image.
Abstract translation: 提供了系统和方法用于基于内容的图像样式化操作中使用的样式示例的选择。 例如，训练图像可用于识别示例风格化图像，其将在对具有某些类型的语义内容的输入图像进行风格化时生成高质量的程式化图像。 在一个示例中，处理设备确定哪个示例风格化图像更适合于使用由训练图像表示的某些类型的语义内容。 响应于接收或以其他方式访问输入图像，处理设备分析输入图像的语义内容，将输入图像与具有相似语义内容的至少一个训练图像匹配，并且选择至少一个先前已经具有的示例风格化图像 与具有该类型的语义内容的一个或多个训练图像匹配。 处理装置使用所选择的示例风格化图像修改输入图像的颜色或对比度信息。
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公开(公告)号：US20160314619A1
公开(公告)日：2016-10-27
申请号：US14695727
申请日：2015-04-24
Applicant: Adobe Systems Incorporated
Inventor： Linjie Luo , Sunil Hadap , Nathan Carr , Kalyan Sunkavalli , Menglei Chai
CPC classification number: G06K9/00221 , G06T7/344 , G06T7/507 , G06T11/00 , G06T17/00 , G06T2207/30201
Abstract: Systems and methods are disclosed herein for 3-Dimensional portrait reconstruction from a single photo. A face portion of a person depicted in a portrait photo is detected and a 3-Dimensional model of the person depicted in the portrait photo constructed. In one embodiment, constructing the 3-Dimensional model involves fitting hair portions of the portrait photo to one or more helices. In another embodiment, constructing the 3-Dimensional model involves applying positional and normal boundary conditions determined based on one or more relationships between face portion shape and hair portion shape. In yet another embodiment, constructing the 3-Dimensional model involves using shape from shading to capture fine-scale details in a form of surface normals, the shape from shading based on an adaptive albedo model and/or a lighting condition estimated based on shape fitting the face portion.
Abstract translation: 本文公开了用于从单张照片进行三维人像重构的系统和方法。 检测肖像照片中描绘的人的面部部分，并且构建在肖像照片中描绘的人的三维模型。 在一个实施例中，构建三维模型涉及将肖像照片的头发部分适合于一个或多个螺旋。 在另一个实施例中，构造三维模型包括应用基于面部部分形状和头发部分形状之间的一个或多个关系确定的位置和正常边界条件。 在另一个实施例中，构造三维模型涉及使用阴影的形状来以表面法线的形式捕获精细尺度的细节，基于自适应反照率模型的阴影形状和/或基于形状拟合估计的照明条件 面部分。
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公开(公告)号：US20160171755A1
公开(公告)日：2016-06-16
申请号：US15053156
申请日：2016-02-25
Applicant: Adobe Systems Incorporated
Inventor： Kevin Karsch , Kalyan Sunkavalli , Sunil Hadap , Nathan Carr , Hailin Jin
CPC classification number: G06T15/506 , G06T7/536 , G06T11/60 , G06T15/50 , G06T19/20 , G06T2207/10024 , G06T2207/10028 , G06T2219/2021
Abstract: Image editing techniques are disclosed that support a number of physically-based image editing tasks, including object insertion and relighting. The techniques can be implemented, for example in an image editing application that is executable on a computing system. In one such embodiment, the editing application is configured to compute a scene from a single image, by automatically estimating dense depth and diffuse reflectance, which respectively form the geometry and surface materials of the scene. Sources of illumination are then inferred, conditioned on the estimated scene geometry and surface materials and without any user input, to form a complete 3D physical scene model corresponding to the image. The scene model may include estimates of the geometry, illumination, and material properties represented in the scene, and various camera parameters. Using this scene model, objects can be readily inserted and composited into the input image with realistic lighting, shadowing, and perspective.
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Patent Agency Ranking
公开(公告)号：US20190042875A1
公开(公告)日：2019-02-07
申请号：US16148166
申请日：2018-10-01
Applicant: Adobe Systems Incorporated
Inventor： Nathan Carr , Kalyan Sunkavalli , Michal Lukac , Elya Shechtman
IPC: G06K9/62
Abstract: The present disclosure is directed toward systems and methods for image patch matching. In particular, the systems and methods described herein sample image patches to identify those image patches that match a target image patch. The systems and methods described herein probabilistically accept image patch proposals as potential matches based on an oracle. The oracle is computationally inexpensive to evaluate but more approximate than similarity heuristics. The systems and methods use the oracle to quickly guide the search to areas of the search space more likely to have a match. Once areas are identified that likely include a match, the systems and methods use a more accurate similarity function to identify patch matches.
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公开(公告)号：US10074033B2
公开(公告)日：2018-09-11
申请号：US15286905
申请日：2016-10-06
Applicant: Adobe Systems Incorporated
Inventor： Nathan Carr , Kalyan Sunkavalli , Michal Lukac , Elya Shechtman
CPC classification number: G06K9/621 , G06K9/38 , G06K2009/6213 , G06T7/337
Abstract: Certain embodiments involve using labels to track high-frequency offsets for patch-matching. For example, a processor identifies an offset between a first source image patch and a first target image patch. If the first source image patch and the first target image patch are sufficiently similar, the processor updates a data structure to include a label specifying the offset. The processor associates, via the data structure, the first source image patch with the label. The processor subsequently selects certain high-frequency offsets, including the identified offset, from frequently occurring offsets in the data structure. The processor uses these offsets to identify a second target image patch, which is located at the identified offset from a second source image patch. The processor associates, via the data structure, the second source image patch with the identified offset based on a sufficient similarity between the second source image patch and the second target image patch.
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公开(公告)号：US20180101942A1
公开(公告)日：2018-04-12
申请号：US15286905
申请日：2016-10-06
Applicant: Adobe Systems Incorporated
Inventor： Nathan Carr , Kalyan Sunkavalli , Michal Lukac , Elya Shechtman
CPC classification number: G06K9/621 , G06K9/38 , G06K2009/6213 , G06T7/003
Abstract: Certain embodiments involve using labels to track high-frequency offsets for patch-matching. For example, a processor identifies an offset between a first source image patch and a first target image patch. If the first source image patch and the first target image patch are sufficiently similar, the processor updates a data structure to include a label specifying the offset. The processor associates, via the data structure, the first source image patch with the label. The processor subsequently selects certain high-frequency offsets, including the identified offset, from frequently occurring offsets in the data structure. The processor uses these offsets to identify a second target image patch, which is located at the identified offset from a second source image patch. The processor associates, via the data structure, the second source image patch with the identified offset based on a sufficient similarity between the second source image patch and the second target image patch.
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公开(公告)号：US09892542B2
公开(公告)日：2018-02-13
申请号：US14946193
申请日：2015-11-19
Applicant: Adobe Systems Incorporated
Inventor： Kalyan Sunkavalli
CPC classification number: G06T15/04 , G06T2200/24 , G06T2210/36
Abstract: This disclosure relates to generating a bump map and/or a normal map from an image. For example, a method for generating a bump map includes receiving a texture image and a plurality of user-specified weights. The method further includes deriving a plurality of images from the texture image, the plurality of images vary from one another with respect to resolution or sharpness. The method further includes weighting individual images of the plurality of images according to the user-specified weights. The method further includes generating a bump map using the weighted individual images. The method further includes providing an image for display with texture added to a surface of an object in the image based on the bump map.
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公开(公告)号：US09613454B2
公开(公告)日：2017-04-04
申请号：US15053156
申请日：2016-02-25
Applicant: Adobe Systems Incorporated
Inventor： Kevin Karsch , Kalyan Sunkavalli , Sunil Hadap , Nathan Carr , Hailin Jin
CPC classification number: G06T15/506 , G06T7/536 , G06T11/60 , G06T15/50 , G06T19/20 , G06T2207/10024 , G06T2207/10028 , G06T2219/2021
Abstract: Image editing techniques are disclosed that support a number of physically-based image editing tasks, including object insertion and relighting. The techniques can be implemented, for example in an image editing application that is executable on a computing system. In one such embodiment, the editing application is configured to compute a scene from a single image, by automatically estimating dense depth and diffuse reflectance, which respectively form the geometry and surface materials of the scene. Sources of illumination are then inferred, conditioned on the estimated scene geometry and surface materials and without any user input, to form a complete 3D physical scene model corresponding to the image. The scene model may include estimates of the geometry, illumination, and material properties represented in the scene, and various camera parameters. Using this scene model, objects can be readily inserted and composited into the input image with realistic lighting, shadowing, and perspective.
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