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    GUIDED IMAGE COMPOSITION ON MOBILE DEVICES
    1.
    发明申请
    GUIDED IMAGE COMPOSITION ON MOBILE DEVICES 审中-公开

    公开(公告)号：US20190109981A1

    公开(公告)日：2019-04-11

    申请号：US15730614

    申请日：2017-10-11

    Applicant: Adobe Systems Incorporated

    Inventor： Jianming Zhang ,  Zijun Wei ,  Zhe Lin ,  Xiaohui Shen ,  Radomir Mech

    IPC: H04N5/232

    CPC classification number: H04N5/232935 ,  G06N3/08 ,  H04N5/23222 ,  H04N5/23229 ,  H04N5/23293

    Abstract: Various embodiments describe facilitating real-time crops on an image. In an example, an image processing application executed on a device receives image data corresponding to a field of view of a camera of the device. The image processing application renders a major view on a display of the device in a preview mode. The major view presents a previewed image based on the image data. The image processing application receives a composition score of a cropped image from a deep-learning system. The image processing application renders a sub-view presenting the cropped image based on the composition score in a preview mode. Based on a user interaction, the image processing application renders the cropped image in the major view with the sub-view in the preview mode.

    Accurate tag relevance prediction for image search
    2.
    发明授权
    Accurate tag relevance prediction for image search 有权

    公开(公告)号：US10235623B2

    公开(公告)日：2019-03-19

    申请号：US15094633

    申请日：2016-04-08

    Applicant: ADOBE SYSTEMS INCORPORATED

    Inventor： Zhe Lin ,  Xiaohui Shen ,  Jonathan Brandt ,  Jianming Zhang ,  Chen Fang

    IPC: G06N99/00 ,  G06F17/30 ,  G06N3/08 ,  G06N3/04

    Abstract: Embodiments of the present invention provide an automated image tagging system that can predict a set of tags, along with relevance scores, that can be used for keyword-based image retrieval, image tag proposal, and image tag auto-completion based on user input. Initially, during training, a clustering technique is utilized to reduce cluster imbalance in the data that is input into a convolutional neural network (CNN) for training feature data. In embodiments, the clustering technique can also be utilized to compute data point similarity that can be utilized for tag propagation (to tag untagged images). During testing, a diversity based voting framework is utilized to overcome user tagging biases. In some embodiments, bigram re-weighting can down-weight a keyword that is likely to be part of a bigram based on a predicted tag set.

    Digital Image Defect Identification and Correction
    3.
    发明申请
    Digital Image Defect Identification and Correction 审中-公开

    公开(公告)号：US20180268533A1

    公开(公告)日：2018-09-20

    申请号：US15458826

    申请日：2017-03-14

    Applicant: Adobe Systems Incorporated

    Inventor： Radomir Mech ,  Ning Yu ,  Xiaohui Shen ,  Zhe Lin

    IPC: G06T7/00 ,  G06T5/00

    CPC classification number: G06T7/0002 ,  G06N3/0454 ,  G06N3/08 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30168

    Abstract: Digital image defect identification and correction techniques are described. In one example, a digital medium environment is configured to identify and correct a digital image defect through identification of a defect in a digital image using machine learning. The identification includes generating a plurality of defect type scores using a plurality of defect type identification models, as part of machine learning, for a plurality of different defect types and determining the digital image includes the defect based on the generated plurality of defect type scores. A correction is generated for the identified defect and the digital image is output as included the generated correction.

    Neural network patch aggregation and statistics
    5.
    发明授权
    Neural network patch aggregation and statistics 有权

    公开(公告)号：US09996768B2

    公开(公告)日：2018-06-12

    申请号：US14548170

    申请日：2014-11-19

    Applicant: Adobe Systems Incorporated

    Inventor： Xiaohui Shen ,  Xin Lu ,  Zhe Lin ,  Radomir Mech

    IPC: G06K9/00 ,  G06K9/46

    CPC classification number: G06K9/4676 ,  G06K9/4628

    Abstract: Neural network patch aggregation and statistical techniques are described. In one or more implementations, patches are generated from an image, e.g., randomly, and used to train a neural network. An aggregation of outputs of patches processed by the neural network may be used to label an image using an image descriptor, such as to label aesthetics of the image, classify the image, and so on. In another example, the patches may be used by the neural network to calculate statistics describing the patches, such as to describe statistics such as minimum, maximum, median, and average of activations of image characteristics of the individual patches. These statistics may also be used to support a variety of functionality, such as to label the image as described above.

    Generating image features based on robust feature-learning
    7.
    发明授权
    Generating image features based on robust feature-learning 有权

    公开(公告)号：US09990558B2

    公开(公告)日：2018-06-05

    申请号：US15705151

    申请日：2017-09-14

    Applicant: Adobe Systems Incorporated

    Inventor： Zhe Lin ,  Xiaohui Shen ,  Jonathan Brandt ,  Jianming Zhang

    IPC: G06K9/62 ,  G06K9/46 ,  G06K9/48 ,  G06N3/08 ,  G06N3/04

    CPC classification number: G06K9/4628 ,  G06K9/6298 ,  G06K2009/00322 ,  G06N3/04 ,  G06N3/08

    Abstract: Techniques for increasing robustness of a convolutional neural network based on training that uses multiple datasets and multiple tasks are described. For example, a computer system trains the convolutional neural network across multiple datasets and multiple tasks. The convolutional neural network is configured for learning features from images and accordingly generating feature vectors. By using multiple datasets and multiple tasks, the robustness of the convolutional neural network is increased. A feature vector of an image is used to apply an image-related operation to the image. For example, the image is classified, indexed, or objects in the image are tagged based on the feature vector. Because the robustness is increased, the accuracy of the generating feature vectors is also increased. Hence, the overall quality of an image service is enhanced, where the image service relies on the image-related operation.

    Patch Partitions and Image Processing
    10.
    发明申请
    Patch Partitions and Image Processing 有权

    公开(公告)号：US20180005354A1

    公开(公告)日：2018-01-04

    申请号：US15707418

    申请日：2017-09-18

    Applicant: Adobe Systems Incorporated

    Inventor： Zhe Lin ,  Jianchao Yang ,  Hailin Jin ,  Xin Lu

    IPC: G06T5/00 ,  G06K9/62 ,  G06K9/00

    CPC classification number: G06T5/005 ,  G06K9/00664 ,  G06K9/6218 ,  G06T5/002 ,  G06T2207/20081 ,  G06T2207/20084

    Abstract: Patch partition and image processing techniques are described. In one or more implementations, a system includes one or more modules implemented at least partially in hardware. The one or more modules are configured to perform operations including grouping a plurality of patches taken from a plurality of training samples of images into respective ones of a plurality of partitions, calculating an image processing operator for each of the partitions, determining distances between the plurality of partitions that describe image similarity of patches of the plurality of partitions, one to another, and configuring a database to provide the determined distance and the image processing operator to process an image in response to identification of a respective partition that corresponds to a patch taken from the image.

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