Object Detection Training Based on Artificially Generated Images

    公开(公告)号:US20200051291A1

    公开(公告)日:2020-02-13

    申请号:US16658513

    申请日:2019-10-21

    Abstract: Technology disclosed herein may involve a computing system that (i) based on an image of a target object of a given class of object and at least one GAN configured to generate artificial images of the given class of object, generates an artificial image of the target object that is substantially similar to real-world images of objects of the given class of objects captured by real-world scanning devices, (ii) based on an image of a receptacle, selects an insertion location within the receptacle in the image of the receptacle to insert the artificial image of the target object, (iii) generates a combined image of the receptacle and the target object, wherein generating the combined image comprises inserting the artificial image of the target object into the image of the receptacle at the insertion location, and (iv) trains one or more object detection algorithms with the combined image of the receptacle and the target object.

    Detection of items
    2.
    发明授权

    公开(公告)号:US10572963B1

    公开(公告)日:2020-02-25

    申请号:US15714932

    申请日:2017-09-25

    Abstract: According to an aspect, a system comprises at least one processor, a memory, and a non-transitory computer-readable storage medium storing instructions. The stored instructions are executable to cause the at least one processor to: receive a digital image that represents an object scanned by a detection device, determine a region of the digital image that is likely to contain an item, transform the region of the digital image to an embedding, classify, based on the embedding, the region as containing a known class of known item, and responsive to classifying the region as containing the known class of item: generate a graphical representation based on the known class of item.

    Generating Graphical Representations of Scanned Objects

    公开(公告)号:US20190019318A1

    公开(公告)日:2019-01-17

    申请号:US15800688

    申请日:2017-11-01

    Abstract: According to an aspect, a system comprises at least one processor, a memory, and a non-transitory computer-readable storage medium storing instructions. The stored instructions are executable to cause the at least one processor to: receive a digital image that represents an object scanned by a security scanning device, receive, from a neural network, information indicating an item identified within the image, receive, from a database, item data for the identified item, and generate, for output at a display, a graphical representation corresponding to the identified item based on the received item data, wherein the graphical representation indicates a location of the identified item by a neural network, and wherein the generated graphical representation comprises at least a portion of the digital image corresponding to the identified item, and output, for display, the graphical representation.

    Multi-perspective detection of objects

    公开(公告)号:US10452959B1

    公开(公告)日:2019-10-22

    申请号:US16189300

    申请日:2018-11-13

    Abstract: Various systems, methods and non-transitory computer-readable media are described, which may involve performing operations comprising: receiving, with an object detector, a first image from a first positional angle comprising a first perspective of a scene, receiving, with the object detector, a second image from a second, different positional angle comprising a second perspective of the scene, and performing, with the object detector, object detection on the first image from the first perspective and on the second image from the second perspective by cross-referencing data related to the first image and the second image within the object detector.

    Multi-Perspective Detection of Objects
    9.
    发明申请

    公开(公告)号:US20200050887A1

    公开(公告)日:2020-02-13

    申请号:US16658934

    申请日:2019-10-21

    Abstract: Technology disclosed herein may involve a computing system that (i) generates (a) a first feature map based on a first visual input from a first perspective of a scene utilizing at least one first neural network and (b) a second feature map based on a second visual input from a second, different perspective of the scene utilizing at least one second neural network, where the first perspective and the second perspective share a common dimension, (ii) based on the first feature map and a portion of the second feature map corresponding to the common dimension, generates cross-referenced data for the first visual input, (iii) based on the second feature map and a portion of the first feature map corresponding to the common dimension, generates cross-referenced data for the second visual input, and (iv) based on the cross-referenced data, performs object detection on the scene.

    Generating synthetic image data
    10.
    发明授权

    公开(公告)号:US10453223B2

    公开(公告)日:2019-10-22

    申请号:US15799274

    申请日:2017-10-31

    Abstract: According to an aspect, a method comprises: generating a 2D projection from a 3D representation of an object, wherein the 2D projection comprises an edgemapped projection of the 3D representation, generating, with a generative adversarial neural network (GAN), and based on the edgemapped projection, a simulated image of the object, wherein the simulated image appears as though the object has been scanned by a detection device, combining the simulated image of the object with a background image to form a synthesized image, wherein the background image was captured by a detection device, and outputting the synthesized image.

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