Abstract: Disclosed are systems, methods, and computer-readable storage media to enhance an image on a mobile computing device. In some aspects, a user interface on the mobile computing device provides a plurality of image filters, each of the image filters associated with a different replacement sky type. Upon application of one of the plurality of image filters to an image, the mobile computing device is configured to identify a sky portion of the image, modify a color mapping of a non-sky portion of the image, and replace the sky portion of the image with replacement sky data corresponding to the applied image filter.

Abstract: An active depth detection system can generate a depth map from an image and user interaction data, such as a pair of clicks. The active depth detection system can be implemented as a recurrent neural network that can receive the user interaction data as runtime inputs after training. The active depth detection system can store the generated depth map for further processing, such as image manipulation or real-world object detection.

Abstract: Disclosed are systems, methods, and computer-readable storage media to enhance an image on a mobile computing device. In some aspects, a user interface on the mobile computing device provides a plurality of image filters, each of the image filters associated with a different replacement sky type. Upon application of one of the plurality of image filters to an image, the mobile computing device is configured to identify a sky portion of the image, modify a color mapping of a non-sky portion of the image, and replace the sky portion of the image with replacement sky data corresponding to the applied image filter.

Abstract: Various embodiments provide for systems, methods, and computer-readable storage media for annotating a digital image with a texture fill. An annotation system may receive a user input defining a border separating a first portion of a target digital image from a second portion of the target digital image. The annotation system may then generate a contour mask, such as a binary mask, for the target digital image based on the user-defined border. The annotation system may then apply a media overlay to the target image based on the contour mask. In particular, the contour mask can define portions of the target digital image such that the annotation system will apply a media overlay to at least one of those portions while not applying the media overlay to remaining portions of the target digital image.

Abstract: Disclosed are systems, methods, and computer-readable storage media to perform automatic image inpainting using local patch statistics. The method includes receiving a user input identifying a user-selected region of an image and determining a local region for the user-selected region. The local region includes a portion of the image outside of the user-selected region and that surrounds the user-selected region. The method may further include identifying patch matches within the local region, and inpainting the user-selected region using some of the patch matches identified within the local region.

Abstract: Various embodiments provide for systems, methods, and computer-readable storage media for annotating a digital image with a texture fill. An annotation system may receive a user input defining a border separating a first portion of a target digital image from a second portion of the target digital image. The annotation system may then generate a contour mask, such as a binary mask, for the target digital image based on the user-defined border. The annotation system may then apply a media overlay to the target image based on the contour mask. In particular, the contour mask can define portions of the target digital image such that the annotation system will apply a media overlay to at least one of those portions while not applying the media overlay to remaining portions of the target digital image.

Abstract: An active depth detection system can generate a depth map from an image and user interaction data, such as a pair of clicks. The active depth detection system can be implemented as a recurrent neural network that can receive the user interaction data as runtime inputs after training. The active depth detection system can store the generated depth map for further processing, such as image manipulation or real-world object detection.

Abstract: Disclosed are systems, methods, and computer-readable storage media to object replacement in an image. The method includes receiving a user input identifying an object depicted in an image. The method further includes removing the object from the image by replacing a first region of the image with one or more patch matches identified from a second region of the image. Each of the one or more patch matches comprises two identical image patches. The second region includes a portion of the image that is outside of the first region and that surrounds the first region. The replacing of the first region with the one or more patch matches identified from the second region yields a modified image without the object.

Abstract: An active depth detection system can generate a depth map from an image and user interaction data, such as a pair of clicks. The active depth detection system can be implemented as a recurrent neural network that can receive the user interaction data as runtime inputs after training. The active depth detection system can store the generated depth map for further processing, such as image manipulation or real-world object detection.

Abstract: Disclosed are systems, methods, and computer-readable storage media to perform an interactive image recolorization process. The method includes receiving user input including a single stroke drawn on an image presented on a client device. The method further includes determining a region of interest in the image based on the user input. The method further includes recolorizing the region of interest on the image and causing presentation of a result of the recolorization on the client device.

Abstract: Various embodiments provide for systems, methods, and computer-readable storage media for annotating a digital image with a texture fill. An annotation system may receive a user input defining a border separating a first portion of a target digital image from a second portion of the target digital image. The annotation system may then generate a contour mask, such as a binary mask, for the target digital image based on the user-defined border. The annotation system may then apply a media overlay to the target image based on the contour mask. In particular, the contour mask can define portions of the target digital image such that the annotation system will apply a media overlay to at least one of those portions while not applying the media overlay to remaining portions of the target digital image.

Abstract: Disclosed are systems, methods, and computer-readable storage media to perform automatic image inpainting using local patch statistics. The method includes receiving a user input identifying a user-selected region of an image and determining a local region for the user-selected region. The local region includes a portion of the image outside of the user-selected region and that surrounds the user-selected region. The method may further include identifying patch matches within the local region, and inpainting the user-selected region using some of the patch matches identified within the local region.

Abstract: Disclosed are systems, methods, and computer-readable storage media to perform an interactive image recolorization process. The method includes receiving user input including a single stroke drawn on an image presented on a client device. The method further includes expanding the single stroke drawn on the image to generate an expanded stroke mask and refining the expanded stroke mask to determine a precise boundary that defines a region of interest on the image. The method further includes recolorizing the region of interest on the image in accordance with a user-specified color and causing presentation of a result of the recolorization on the client device.

Abstract: Disclosed are systems, methods, and computer-readable storage media to perform automatic image inpainting using local patch statistics. The method includes receiving a user input identifying a user-selected region of an image and determining a local region for the user-selected region. The local region includes a portion of the image outside of the user-selected region and that surrounds the user-selected region. The method may further include enlarging the local region by a predefined padding size, and scaling the user-selected region to a predetermined size. The method may further include identifying patch matches within the local region, and inpainting the user-selected region using some of the patch matches identified within the local region.

Abstract: This disclosure provides method and systems of classifying a digital image of an object. Specifically, according to one exemplary embodiment, an object classifier is trained using a constrained MI-SVM (multiple instance-support vector machine) approach whereby training images of objects are sampled to generate a collection of image regions associated with an object type and viewpoint, and the classifier is trained to determine an appropriate mid-level representation of the training image which is discriminative.

Abstract: This disclosure provides method and systems of classifying a digital image of an object. Specifically, according to one exemplary embodiment, an object classifier is trained using a constrained MI-SVM (multiple instance-support vector machine) approach whereby training images of objects are sampled to generate a collection of image regions associated with an object type and viewpoint, and the classifier is trained to determine an appropriate mid-level representation of the training image which is discriminative.