Abstract: Embodiments are disclosed for generating lens blur effects. The disclosed systems and methods comprise receiving a request to apply a lens blur effect to an image, the request identifying an input image and a first disparity map, generating a plurality of disparity maps and a plurality of distance maps based on the first disparity map, splatting influences of pixels of the input image using a plurality of reshaped kernel gradients, gathering aggregations of the splatted influences, and determining a lens blur for a first pixel of the input image in an output image based on the gathered aggregations of the splatted influences.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that generate refined segmentation masks for digital visual media items. For example, in one or more embodiments, the disclosed systems utilize a segmentation refinement neural network to generate an initial segmentation mask for a digital visual media item. The disclosed systems further utilize the segmentation refinement neural network to generate one or more refined segmentation masks based on uncertainly classified pixels identified from the initial segmentation mask. To illustrate, in some implementations, the disclosed systems utilize the segmentation refinement neural network to redetermine whether a set of uncertain pixels corresponds to one or more objects depicted in the digital visual media item based on low-level (e.g., local) feature values extracted from feature maps generated for the digital visual media item.

Abstract: Embodiments are disclosed for generating lens blur effects. The disclosed systems and methods comprise receiving a request to apply a lens blur effect to an image, the request identifying an input image and a first disparity map, generating a plurality of disparity maps and a plurality of distance maps based on the first disparity map, splatting influences of pixels of the input image using a plurality of reshaped kernel gradients, gathering aggregations of the splatted influences, and determining a lens blur for a first pixel of the input image in an output image based on the gathered aggregations of the splatted influences.

Abstract: Embodiments are disclosed for generating lens blur effects. The disclosed systems and methods comprise receiving a request to apply a lens blur effect to an image, the request identifying an input image and a first disparity map, generating a plurality of disparity maps and a plurality of distance maps based on the first disparity map, splatting influences of pixels of the input image using a plurality of reshaped kernel gradients, gathering aggregations of the splatted influences, and determining a lens blur for a first pixel of the input image in an output image based on the gathered aggregations of the splatted influences.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that generate refined segmentation masks for digital visual media items. For example, in one or more embodiments, the disclosed systems utilize a segmentation refinement neural network to generate an initial segmentation mask for a digital visual media item. The disclosed systems further utilize the segmentation refinement neural network to generate one or more refined segmentation masks based on uncertainly classified pixels identified from the initial segmentation mask. To illustrate, in some implementations, the disclosed systems utilize the segmentation refinement neural network to redetermine whether a set of uncertain pixels corresponds to one or more objects depicted in the digital visual media item based on low-level (e.g., local) feature values extracted from feature maps generated for the digital visual media item.

Abstract: Methods and apparatus for retargeting and prioritized interpolation of lens profiles. A lens profile file may include a set of lens sub-profiles. The camera body and/or settings described in the file may not exactly match that of camera body and/or settings used to capture a target image. A sub-profile processing module may perform a prioritized sub-profile sorting and interpolation method to generate an interpolated sub-profile that may be applied to the target image to correct aberrations including, but not limited to, geometric distortion, lateral chromatic aberration, and vignette. Thus, models generated for a reference camera at a variety of settings may be applied to a target image captured with the same type of lens but with a different camera and/or with different settings that are not exactly modeled in the lens profile file.

Abstract: Embodiments are disclosed for generating lens blur effects. The disclosed systems and methods comprise receiving a request to apply a lens blur effect to an image, the request identifying an input image and a first disparity map, generating a plurality of disparity maps and a plurality of distance maps based on the first disparity map, splatting influences of pixels of the input image using a plurality of reshaped kernel gradients, gathering aggregations of the splatted influences, and determining a lens blur for a first pixel of the input image in an output image based on the gathered aggregations of the splatted influences.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that generate refined segmentation masks for digital visual media items. For example, in one or more embodiments, the disclosed systems utilize a segmentation refinement neural network to generate an initial segmentation mask for a digital visual media item. The disclosed systems further utilize the segmentation refinement neural network to generate one or more refined segmentation masks based on uncertainly classified pixels identified from the initial segmentation mask. To illustrate, in some implementations, the disclosed systems utilize the segmentation refinement neural network to redetermine whether a set of uncertain pixels corresponds to one or more objects depicted in the digital visual media item based on low-level (e.g., local) feature values extracted from feature maps generated for the digital visual media item.

Abstract: Content creation suggestion techniques are described. In one or more implementations, techniques are implemented to generate suggestions that are usable to guide creative professionals in the creation of content such as images, video, sound, multimedia, and so forth. A variety of techniques are usable to generate suggestions for the content professionals. In a first such example, suggestions are based on shared characteristics of images obtained by users of a content sharing service, e.g., licensed by the users. In another example, suggestions are generated by the content sharing service based on keywords used to locate the images. In a further example, suggestions are generated based on data described communications performed using social network services. In yet another example, recognition of failure of search is used to generate suggestions. A variety of other examples are also contemplated and described herein.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that generate refined segmentation masks for digital visual media items. For example, in one or more embodiments, the disclosed systems utilize a segmentation refinement neural network to generate an initial segmentation mask for a digital visual media item. The disclosed systems further utilize the segmentation refinement neural network to generate one or more refined segmentation masks based on uncertainly classified pixels identified from the initial segmentation mask. To illustrate, in some implementations, the disclosed systems utilize the segmentation refinement neural network to redetermine whether a set of uncertain pixels corresponds to one or more objects depicted in the digital visual media item based on low-level (e.g., local) feature values extracted from feature maps generated for the digital visual media item.

Abstract: Facial skin mask generated by a digital content creation system is described. The digital content creation system includes digital effects on skin in facial regions of digital content with efficiency and accuracy. Upon identifying a facial region within digital content, the system generates a first regional skin mask, a second regional skin mask, and combines both of the first and second regional skin masks to generate a facial skin mask indicative of skin of the identified facial regions depicted in digital content. The digital content creation system then modifies digital content by applying user selected digital effects to the skin of the facial region using the generated facial skin mask.

Abstract: Content creation and licensing control techniques are described. In a first example, a content creation service is configured to support content creation using an image along with functionality to locate the image or a similar image that is available for licensing. In another example, previews of images are used to generate different versions of content along with an option to license images previewed in an approved version of the content. In a further example, fingerprints are used to locate images used as part of content creation by a content creation service without leaving a context of the service. In yet another example, location of licensable versions of images is based at least in part on identification of a watermark included as part of an image. In an additional example, an image itself is used as a basis to locate other images available for licensing by a content sharing service.

Abstract: Facial skin mask generated by a digital content creation system is described. The digital content creation system includes digital effects on skin in facial regions of digital content with efficiency and accuracy. Upon identifying a facial region within digital content, the system generates a first regional skin mask, a second regional skin mask, and combines both of the first and second regional skin masks to generate a facial skin mask indicative of skin of the identified facial regions depicted in digital content. The digital content creation system then modifies digital content by applying user selected digital effects to the skin of the facial region using the generated facial skin mask.

Abstract: Image search persona techniques and systems are described. In one or more implementations, a digital medium environment is described for controlling image searches by one or more computing devices. An image search request and an indication of one or more personas of one or more respective users associated with the image search request is received by the one or more computing devices. The one or more personas specify characteristics of the one or more respective users themselves. A plurality of images are obtained by the one or more computing devices based on the image search request. The plurality of images are filtered by the one or more computing devices based on the one or more personas and a search result is generated by the one or more computing devices from the filtered plurality of images.

Abstract: Content creation suggestion techniques are described. In one or more implementations, techniques are implemented to generate suggestions that are usable to guide creative professionals in the creation of content such as images, video, sound, multimedia, and so forth. A variety of techniques are usable to generate suggestions for the content professionals. In a first such example, suggestions are based on shared characteristics of images obtained by users of a content sharing service, e.g., licensed by the users. In another example, suggestions are generated by the content sharing service based on keywords used to locate the images. In a further example, suggestions are generated based on data described communications performed using social network services. In yet another example, recognition of failure of search is used to generate suggestions. A variety of other examples are also contemplated and described herein.

Abstract: Content creation suggestion techniques are described. In one or more implementations, techniques are implemented to generate suggestions that are usable to guide creative professionals in the creation of content such as images, video, sound, multimedia, and so forth. A variety of techniques are usable to generate suggestions for the content professionals. In a first such example, suggestions are based on shared characteristics of images obtained by users of a content sharing service, e.g., licensed by the users. In another example, suggestions are generated by the content sharing service based on keywords used to locate the images. In a further example, suggestions are generated based on data described communications performed using social network services. In yet another example, recognition of failure of search is used to generate suggestions. A variety of other examples are also contemplated and described herein.

Abstract: Usage based content search result techniques are described. In one or more implementations, a digital medium environment controls image searches and availability by one or more computing devices. A search is performed by the one or more computing devices to locate images made available via a network by a content sharing service responsive to one or more inputs received from a user. A search result is configured by the one or more computing devices that includes the plurality of images based at least in part on an amount of usage of respective said images by other users of the content sharing service. Output of the search result is controlled via a user interface by the one or more computing devices to the user of the content sharing service.

Abstract: Methods and apparatus for constraining solution space in image processing techniques may use the metadata for a set of images to constrain an image processing solution to a smaller solution space. In one embodiment, a process may require N parameters for processing an image. A determination may be made from metadata that multiple images were captured with the same camera/lens and with the same settings. A set of values may be estimated for the N parameters from data in one or more of the images. The process may then be applied to each of images using the set of values. In one embodiment, a value for a parameter of a process may be estimated for an image. If the estimated value deviates substantially from a value for the parameter in the metadata, the metadata value is used in the process instead of the estimated value.

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed towards automatic selection of regions for blur kernel estimation. In one embodiment, a process divides a blurred image into a regions. From these regions a first region and a second region can be selected based on a number of edge orientations within the selected regions. A first blur kernel can then be estimated based on the first region and a second blur kernel can be estimated for the second region. The first and second blur kernel can then be utilized to respectively deblur a first and second portion of the image to produce a deblurred image. Other embodiments may be described and/or claimed.

Abstract: Content creation and licensing control techniques are described. In a first example, a content creation service is configured to support content creation using an image along with functionality to locate the image or a similar image that is available for licensing. In another example, previews of images are used to generate different versions of content along with an option to license images previewed in an approved version of the content. In a further example, fingerprints are used to locate images used as part of content creation by a content creation service without leaving a context of the service. In yet another example, location of licensable versions of images is based at least in part on identification of a watermark included as part of an image. In an additional example, an image itself is used as a basis to locate other images available for licensing by a content sharing service.