Abstract: An implant includes a curved first plate section having a curvature about a longitudinal axis extending in a longitudinal direction. The first plate section has a first hole and a second hole. The first hole and the second hole are positioned to receive respective bone screws for attaching the implant to a first curved surface of a bone having a syndesmosis. A second plate section extends continuously from the first plate section. The second plate section has at least a third hole that is positioned to be offset from the first hole and the second hole in a direction that is anterior or posterior from the first hole and the second hole in a case where the longitudinal axis is aligned along a superior-inferior direction. The third hole is configured to receive at least one screw or at least one button for holding a suture at a position offset from the first line segment hole and the second hole in the anterior or posterior direction, for reducing the syndesmosis.

Abstract: Techniques and systems are described to model and extract knowledge from images. A digital medium environment is configured to learn and use a model to compute a descriptive summarization of an input image automatically and without user intervention. Training data is obtained to train a model using machine learning in order to generate a structured image representation that serves as the descriptive summarization of an input image. The images and associated text are processed to extract structured semantic knowledge from the text, which is then associated with the images. The structured semantic knowledge is processed along with corresponding images to train a model using machine learning such that the model describes a relationship between text features within the structured semantic knowledge. Once the model is learned, the model is usable to process input images to generate a structured image representation of the image.

Abstract: Techniques and systems are described to recolor a group of images for color consistency. Techniques include extracting color palettes for images of the group of images and generating a group theme color palette based on the color palettes for the images. Image color palettes are then mapped to the group theme color palette and the images are modified in response to the mapping. In some examples, the mapping includes discouraging multiple colors of a single color palette from mapping to a single color of the group theme color palette. Additionally, or alternatively, the mapping includes discouraging a forced mapping of a dissimilar color of an image color palette from mapping to the group theme color palette.

Abstract: Stereo correspondence and depth sensor techniques are described. In one or more implementations, a depth map generated by a depth sensor is leveraged as part of processing of stereo images to assist in identifying which parts of stereo images correspond to each other. The depth map, for instance, may be utilized to assist in identifying depth discontinuities in the stereo images. Additionally, techniques may be employed to align the depth discontinuities identified from the depth map to image edges identified from the stereo images. Techniques may also be employed to suppress image edges that do not correspond to the depth discontinuities of the depth map in comparison with image edges that do correspond to the depth discontinuities as part of the identification.

Abstract: Image search techniques and systems involving emotions are described. In one or more implementations, a digital medium environment of a content sharing service is described for image search result configuration and control based on a search request that indicates an emotion. The search request is received that includes one or more keywords and specifies an emotion. Images are located that are available for licensing by matching one or more tags associated with the image with the one or more keywords and as corresponding to the emotion. The emotion of the images is identified using one or more models that are trained using machine learning based at least in part on training images having tagged emotions. Output is controlled of a search result having one or more representations of the images that are selectable to license respective images from the content sharing service.

Abstract: Stereo correspondence and depth sensor techniques are described. In one or more implementations, a depth map generated by a depth sensor is leveraged as part of processing of stereo images to assist in identifying which parts of stereo images correspond to each other. The depth map, for instance, may be utilized to assist in identifying depth discontinuities in the stereo images. Additionally, techniques may be employed to align the depth discontinuities identified from the depth map to image edges identified from the stereo images. Techniques may also be employed to suppress image edges that do not correspond to the depth discontinuities of the depth map in comparison with image edges that do correspond to the depth discontinuities as part of the identification.

Abstract: Techniques and systems are described to support digital image processing through use of an image repository, e.g., a stock image database or other storage. In one example, a plurality of candidate digital images are obtained from an image repository based on a target digital image. A plurality of transformations are generated to be applied to the target digital image, each transformation based on a respective candidate digital image. Semantic information is employed as part of the transformations, e.g., blending, filtering, or alignment. A plurality of transformed target digital images are generated based at least in part through application of the plurality of transformations to the target image.

Abstract: Techniques and systems are described to model and extract knowledge from images. A digital medium environment is configured to learn and use a model to compute a descriptive summarization of an input image automatically and without user intervention. Training data is obtained to train a model using machine learning in order to generate a structured image representation that serves as the descriptive summarization of an input image. The images and associated text are processed to extract structured semantic knowledge from the text, which is then associated with the images. The structured semantic knowledge is processed along with corresponding images to train a model using machine learning such that the model describes a relationship between text features within the structured semantic knowledge. Once the model is learned, the model is usable to process input images to generate a structured image representation of the image.

Abstract: Stereo correspondence and depth sensor techniques are described. In one or more implementations, a depth map generated by a depth sensor is leveraged as part of processing of stereo images to assist in identifying which parts of stereo images correspond to each other. The depth map, for instance, may be utilized to assist in identifying depth discontinuities in the stereo images. Additionally, techniques may be employed to align the depth discontinuities identified from the depth map to image edges identified from the stereo images. Techniques may also be employed to suppress image edges that do not correspond to the depth discontinuities of the depth map in comparison with image edges that do correspond to the depth discontinuities as part of the identification.

Abstract: Techniques and systems are described to recolor a group of images for color consistency. Techniques include extracting color palettes for images of the group of images and generating a group theme color palette based on the color palettes for the images. Image color palettes are then mapped to the group theme color palette and the images are modified in response to the mapping. In some examples, the mapping includes discouraging multiple colors of a single color palette from mapping to a single color of the group theme color palette. Additionally, or alternatively, the mapping includes discouraging a forced mapping of a dissimilar color of an image color palette from mapping to the group theme color palette.

Abstract: Content creation and sharing integration techniques and systems are described. In one or more implementations, techniques are described in which modifiable versions of content (e.g., images) are created and shared via a content sharing service such that image creation functionality used to create the images is preserved to permit continued creation using this functionality. In one or more additional implementations, image creation functionality employed by a creative professional to create content is leveraged to locate similar images from a content sharing service.

Abstract: Techniques and systems are described to recolor a group of images for color consistency. Techniques include extracting color palettes for images of the group of images and generating a group theme color palette based on the color palettes for the images. Image color palettes are then mapped to the group theme color palette and the images are modified in response to the mapping. In some examples, the mapping includes discouraging multiple colors of a single color palette from mapping to a single color of the group theme color palette. Additionally, or alternatively, the mapping includes discouraging a forced mapping of a dissimilar color of an image color palette from mapping to the group theme color palette.

Abstract: Image depth inference techniques and systems from semantic labels are described. In one or more implementations, a digital medium environment includes one or more computing devices to control a determination of depth within an image. Regions of the image are semantically labeled by the one or more computing devices. At least one of the semantically labeled regions is decomposed into a plurality of segments formed as planes generally perpendicular to a ground plane of the image. Depth of one or more of the plurality of segments is then inferred based on relationships of respective segments with respective locations of the ground plane of the image. A depth map is formed that describes depth for the at least one semantically labeled region based at least in part on the inferred depths for the one or more of the plurality of segments.

Abstract: Techniques and systems are described to support digital image processing through use of an image repository, e.g., a stock image database or other storage. In one example, a plurality of candidate digital images are obtained from an image repository based on a target digital image. A plurality of transformations are generated to be applied to the target digital image, each transformation based on a respective candidate digital image. Semantic information is employed as part of the transformations, e.g., blending, filtering, or alignment. A plurality of transformed target digital images are generated based at least in part through application of the plurality of transformations to the target image.

Abstract: Content creation and sharing integration techniques and systems are described. In one or more implementations, techniques are described in which modifiable versions of content (e.g., images) are created and shared via a content sharing service such that image creation functionality used to create the images is preserved to permit continued creation using this functionality. In one or more additional implementations, image creation functionality employed by a creative professional to create content is leveraged to locate similar images from a content sharing service.

Abstract: Stereo correspondence model fitting techniques are described. In one or more implementations, a model may be fit to a region in at least one of a plurality of stereoscopic images of an image scene. The model may then be used as part of a stereo correspondence calculation, which may include computing disparities for the region based at least in part on correspondence to the model.

Abstract: Techniques and systems are described to support digital image processing through use of an image repository, e.g., a stock image database or other storage. In one example, a plurality of candidate digital images are obtained from an image repository based on a target digital image. A plurality of transformations are generated to be applied to the target digital image, each transformation based on a respective candidate digital image. Semantic information is employed as part of the transformations, e.g., blending, filtering, or alignment. A plurality of transformed target digital images are generated based at least in part through application of the plurality of transformations to the target image.

Abstract: Content creation collection and navigation techniques and systems are described. In one example, a representative image is used by a content sharing service to interact with a collection of images provided as part of a search result. In another example, a user interface image navigation control is configured to support user navigation through images based on one or more metrics. In a further example, a user interface image navigation control is configured to support user navigation through images based on one or more metrics identified for an object selected from the image. In yet another example, collections of images are leveraged as part of content creation. In another example, data obtained from a content sharing service is leveraged to indicate suitability of images of a user for licensing as part of the service.

Abstract: User input-based object selection using multiple visual cues is described. User selection input is received for selecting a portion of an image. Once the user selection input is received, one of a plurality of visual cues that convey different information about content depicted in the image is selected for each pixel. The one visual cue is selected as a basis for identifying the pixel as part of the selected portion of the image or part of an unselected remainder of the image. The visual cues are selected by determining confidences, based in part on the user selection input, that the plurality of visual cues can be used to discriminate whether the pixel is part of the selected portion or part of the remainder. The information conveyed by the selected visual cues is used to identify the pixels as part of the selected portion or part of the remainder.

Abstract: Techniques and systems are described to support digital image processing through use of an image repository, e.g., a stock image database or other storage. In one example, a plurality of candidate digital images are obtained from an image repository based on a target digital image. A plurality of transformations are generated to be applied to the target digital image, each transformation based on a respective candidate digital image. Semantic information is employed as part of the transformations, e.g., blending, filtering, or alignment. A plurality of transformed target digital images are generated based at least in part through application of the plurality of transformations to the target image.