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公开(公告)号：US09025822B2
公开(公告)日：2015-05-05
申请号：US13794125
申请日：2013-03-11
Applicant: Adobe Systems Incorporated
Inventor： Hailin Jin , Zhuoyuan Chen , Zhe Lin , Scott D. Cohen
CPC classification number: G06K9/4642 , G06T7/238 , G06T2207/10016 , G06T2207/20016 , G06T2207/20021
Abstract: In embodiments of spatially coherent nearest neighbor fields, initial matching patches of a nearest neighbor field can be determined at image grid locations of a first digital image and a second digital image. Spatial coherency can be enforced for each matching patch in the second digital image with reference to respective matching patches in the first digital image based on motion data of neighboring matching patches. A multi-resolution iterative process can then update each spatially coherent matching patch based on overlapping grid regions of the matching patches that are evaluated for matching regions of the first and second digital images. An optimal, spatially coherent matching patch can be selected for each of the image grid locations of the first and second digital images based on iterative interaction to enforce the spatial coherency of each matching patch and the multi-resolution iterative process to update each spatially coherent matching patch.
Abstract translation: 在空间相干最近邻域的实施例中，可以在第一数字图像和第二数字图像的图像网格位置处确定最近邻域的初始匹配块。 基于相邻匹配补丁的运动数据，参考第一数字图像中的相应匹配补丁，可以针对第二数字图像中的每个匹配补丁实施空间一致性。 然后，多分辨率迭代过程可以基于为第一和第二数字图像的匹配区域评估的匹配块的重叠网格区域来更新每个空间相干匹配块。 可以基于迭代交互来选择针对第一和第二数字图像的每个图像网格位置的最佳空间相干匹配块，以强制每个匹配块的空间一致性和多分辨率迭代过程以更新每个空间相干匹配 补丁。
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公开(公告)号：US20150117783A1
公开(公告)日：2015-04-30
申请号：US14062559
申请日：2013-10-24
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Radomir Mech , Peng Wang
IPC: G06K9/46
CPC classification number: G06K9/4671 , G06T7/11 , G06T7/136 , G06T7/162 , G06T7/194 , G06T2207/20004 , G06T2207/20016 , G06T2207/20076 , G06T2207/20081
Abstract: In techniques for iterative saliency map estimation, a salient regions module applies a saliency estimation technique to compute a saliency map of an image that includes image regions. A salient image region of the image is determined from the saliency map, and an image region that corresponds to the salient image region is removed from the image. The salient regions module then iteratively determines subsequent salient image regions of the image utilizing the saliency estimation technique to recompute the saliency map of the image with the image region removed, and removes the image regions that correspond to the subsequent salient image regions from the image. The salient image regions of the image are iteratively determined until no salient image regions are detected in the image, and a salient features map is generated that includes each of the salient image regions determined iteratively and combined to generate the final saliency map.
Abstract translation: 在迭代显着性图估计技术中，显着区域模块应用显着性估计技术来计算包括图像区域的图像的显着性图。 从显着性图确定图像的显着图像区域，并且从图像中去除对应于显着图像区域的图像区域。 显着区域模块然后使用显着性估计技术迭代地确定图像的随后的显着图像区域，以重新计算去除图像区域的图像的显着图，并且从图像中去除与后续显着图像区域相对应的图像区域。 迭代地确定图像的显着图像区域，直到在图像中没有检测到显着的图像区域，并且生成包括迭代地确定并组合的每个显着图像区域以产生最终显着图的显着特征图。
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公开(公告)号：US20140247996A1
公开(公告)日：2014-09-04
申请号：US13781988
申请日：2013-03-01
Applicant: ADOBE SYSTEMS INCORPORATED
Inventor： Zhe Lin , Jonathan Brandt , Xiaohui Shen
IPC: G06K9/62
CPC classification number: G06F17/30259 , G06K9/00228 , G06K9/4676 , G06K9/6211 , G06K9/6292
Abstract: One exemplary embodiment involves receiving a test image generating, by a plurality of maps for the test image based on a plurality of object images. Each of the object images comprises an object of a same object type, e.g., each comprising a different face. Each of the plurality of maps is generated to provide information about the similarity of at least a portion of a respective object image to each of a plurality of portions of the test image. The exemplary embodiment further comprises detecting a test image object within the test image based at least in part on the plurality of maps.
Abstract translation: 一个示例性实施例涉及通过基于多个对象图像的测试图像的多个映射来接收测试图像。 每个对象图像包括相同对象类型的对象，例如，每个对象包括不同的面。 生成多个地图中的每一个以提供关于相应对象图像的至少一部分与测试图像的多个部分中的每一个相似度的信息。 该示例性实施例还包括至少部分地基于多个地图检测测试图像内的测试图像对象。
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公开(公告)号：US20140169684A1
公开(公告)日：2014-06-19
申请号：US13713729
申请日：2012-12-13
Applicant: ADOBE SYSTEMS INCORPORATED
Inventor： Kevin Armin Samii , Zhe Lin , Radomir Mech
IPC: G06K9/62
CPC classification number: G06K9/6202 , G06K9/48 , G06K9/6215
Abstract: Systems and methods are provided for generating a distance metric. An image manipulation application receives first and second input images. The image manipulation application generates first and second sets of points corresponding to respective edges of a first object in the first input image and a second object in the second input image. The image manipulation application determines costs of arcs connecting each point from the first set to each point of the second set based on point descriptors for each point of each arc. The image manipulation application determines a minimum set of costs between the first set and the second set that includes a cost of each arc connecting each point of the second set to a point in the first set. The image manipulation application obtains, based at least in part on the minimum set of costs, a distance metric for first and second input images.
Abstract translation: 提供了用于产生距离度量的系统和方法。 图像处理应用接收第一和第二输入图像。 图像处理应用产生与第一输入图像中的第一对象的相应边缘相对应的第一和第二组点，以及第二输入图像中的第二对象。 图像处理应用程序确定基于每个弧的每个点的点描述符将每个点从第一组连接到第二组的每个点的弧的成本。 图像处理应用程序确定第一组和第二组之间的最小成本集合，其包括将第二组的每个点连接到第一组中的点的每个弧的成本。 图像处理应用至少部分地基于最小成本集获得第一和第二输入图像的距离度量。
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公开(公告)号：US20140153817A1
公开(公告)日：2014-06-05
申请号：US13691212
申请日：2012-11-30
Applicant: ADOBE SYSTEMS INCORPORATED
Inventor： Zhe Lin , Xin Lu , Jonathan Brandt , Hailin Jin
CPC classification number: G06K9/68 , G06T5/001 , G06T2207/20021
Abstract: Systems and methods are provided for providing patch size adaptation for patch-based image enhancement operations. In one embodiment, an image manipulation application receives an input image. The image manipulation application compares a value for an attribute of at least one input patch of the input image to a threshold value. Based on comparing the value for the to the threshold value, the image manipulation application adjusts a first patch size of the input patch to a second patch size that improves performance of a patch-based image enhancement operation as compared to the first patch size. The image manipulation application performs the patch-based image enhancement operation based on one or more input patches of the input image having the second patch size.
Abstract translation: 提供了系统和方法，用于为基于贴片的图像增强操作提供补丁大小适配。 在一个实施例中，图像处理应用接收输入图像。 图像处理应用将输入图像的至少一个输入片段的属性的值与阈值进行比较。 基于比较阈值的值，图像处理应用程序将输入补丁的第一补丁大小调整为与第一补丁大小相比提高基于补丁的图像增强操作的性能的第二补丁大小。 图像处理应用程序基于具有第二补丁大小的输入图像的一个或多个输入补丁执行基于补丁的图像增强操作。
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Patent Agency Ranking
公开(公告)号：US20190114748A1
公开(公告)日：2019-04-18
申请号：US15785359
申请日：2017-10-16
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Xin Lu , Xiaohui Shen , Jimei Yang , Jiahui Yu
Abstract: Digital image completion using deep learning is described. Initially, a digital image having at least one hole is received. This holey digital image is provided as input to an image completer formed with a framework that combines generative and discriminative neural networks based on learning architecture of the generative adversarial networks. From the holey digital image, the generative neural network generates a filled digital image having hole-filling content in place of holes. The discriminative neural networks detect whether the filled digital image and the hole-filling digital content correspond to or include computer-generated content or are photo-realistic. The generating and detecting are iteratively continued until the discriminative neural networks fail to detect computer-generated content for the filled digital image and hole-filling content or until detection surpasses a threshold difficulty. Responsive to this, the image completer outputs the filled digital image with hole-filling content in place of the holey digital image's holes.
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公开(公告)号：US20190108640A1
公开(公告)日：2019-04-11
申请号：US15730564
申请日：2017-10-11
Applicant: Adobe Systems Incorporated
Inventor： Jianming Zhang , Zijun Wei , Zhe Lin , Xiaohui Shen , Radomir Mech
Abstract: Various embodiments describe using a neural network to evaluate image crops in substantially real-time. In an example, a computer system performs unsupervised training of a first neural network based on unannotated image crops, followed by a supervised training of the first neural network based on annotated image crops. Once this first neural network is trained, the computer system inputs image crops generated from images to this trained network and receives composition scores therefrom. The computer system performs supervised training of a second neural network based on the images and the composition scores.
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公开(公告)号：US10198801B2
公开(公告)日：2019-02-05
申请号：US15392162
申请日：2016-12-28
Applicant: Adobe Systems Incorporated
Inventor： Jianchao Yang , Zhe Lin
Abstract: Systems and methods are provided for image enhancement using self-examples in combination with external examples. In one embodiment, an image manipulation application receives an input image patch of an input image. The image manipulation application determines a first weight for an enhancement operation using self-examples and a second weight for an enhancement operation using external examples. The image manipulation application generates a first interim output image patch by applying the enhancement operation using self-examples to the input image patch and a second interim output image patch by applying the enhancement operation using external examples to the input image patch. The image manipulation application generates an output image patch by combining the first and second interim output image patches as modified using the first and second weights.
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公开(公告)号：US20180357803A1
公开(公告)日：2018-12-13
申请号：US15620636
申请日：2017-06-12
Applicant: ADOBE SYSTEMS INCORPORATED
Inventor： Jianming Zhang , Zhe Lin , Radomir Mech , Xiaohui Shen
CPC classification number: G06T11/60 , G06T3/40 , G06T7/11 , G06T2210/22
Abstract: Embodiments of the present invention are directed to facilitating region of interest preservation. In accordance with some embodiments of the present invention, a region of interest preservation score using adaptive margins is determined. The region of interest preservation score indicates an extent to which at least one region of interest is preserved in a candidate image crop associated with an image. A region of interest positioning score is determined that indicates an extent to which a position of the at least one region of interest is preserved in the candidate image crop associated with the image. The region of interest preservation score and/or the preserving score are used to select a set of one or more candidate image crops as image crop suggestions.
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公开(公告)号：US20180268548A1
公开(公告)日：2018-09-20
申请号：US15458887
申请日：2017-03-14
Applicant: ADOBE SYSTEMS INCORPORATED
Inventor： Zhe Lin , Xin Lu , Xiaohui Shen , Jimei Yang , Chenxi Liu
Abstract: The invention is directed towards segmenting images based on natural language phrases. An image and an n-gram, including a sequence of tokens, are received. An encoding of image features and a sequence of token vectors are generated. A fully convolutional neural network identifies and encodes the image features. A word embedding model generates the token vectors. A recurrent neural network (RNN) iteratively updates a segmentation map based on combinations of the image feature encoding and the token vectors. The segmentation map identifies which pixels are included in an image region referenced by the n-gram. A segmented image is generated based on the segmentation map. The RNN may be a convolutional multimodal RNN. A separate RNN, such as a long short-term memory network, may iteratively update an encoding of semantic features based on the order of tokens. The first RNN may update the segmentation map based on the semantic feature encoding.
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