Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for providing a mixed level-of-detail rendering of a vector graphics document for display and modification via a client device while downloading and rendering the full vector graphics document. In particular, the disclosed systems download, in response to a request to load a vector graphics document at a client device, a raster image of the vector graphics document. Moreover, the disclosed systems select and download a vector graphic subunit of the vector graphics document, for example, by selecting a priority graphic design layout boundary. Furthermore, the disclosed systems provide, for display via the client device, a mixed level-of-detail rendering comprising the raster image of the vector graphics document and the vector graphic subunit as an overlay of the raster image such that the client device can modify the vector graphic subunit while downloading an additional vector graphic subunit.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for removing objects from an image stream at capture time of a digital image. For example, the disclosed system contemporaneously detects and segments objects from a digital image stream being previewed in a camera viewfinder graphical user interface of a client device. The disclosed system removes selected objects from the image stream and fills a hole left by the removed object with a content aware fill. Moreover, the disclosed system displays the image stream with the removed object and content fill as the image stream is previewed by a user prior to capturing a digital image from the image stream.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for removing objects from an image stream at capture time of a digital image. For example, the disclosed system contemporaneously detects and segments objects from a digital image stream being previewed in a camera viewfinder graphical user interface of a client device. The disclosed system removes selected objects from the image stream and fills a hole left by the removed object with a content aware fill. Moreover, the disclosed system displays the image stream with the removed object and content fill as the image stream is previewed by a user prior to capturing a digital image from the image stream.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for prioritized downloading and rendering of digital vector file components. Specifically, in one or more embodiments, the disclosed systems determine, in connection with accessing a digital vector file, one or more artboards corresponding to one or more portions of a canvas area within the digital vector file. Additionally, the disclosed systems determine, by the at least one processor and for a selected artboard of the one or more artboards according to a download priority, a layer list comprising one or more components associated with the selected artboard. Further, the disclosed systems retrieve, for display, the selected artboard with the one or more components indicated in the layer list by accessing the one or more components associated with the selected artboard according to the download priority.

Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods for detecting and indicating modifications between a digital image and a modified version of a digital image. For example, the disclosed systems generates an ordered collection of change records in response to detecting modifications to the digital image. The disclosed systems generates determine one or more non-contiguous modified regions of pixels in the digital image based on the change records. The disclosed system generate an edited region indicator corresponding to the non-contiguous modified regions. The disclosed systems can further color-code the edited region indicator at an object level based on objects in the modified version of the digital image.

Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods for detecting and indicating modifications between a digital image and a modified version of a digital image. For example, the disclosed systems generates an ordered collection of change records in response to detecting modifications to the digital image. The disclosed systems generates determine one or more non-contiguous modified regions of pixels in the digital image based on the change records. The disclosed system generate an edited region indicator corresponding to the non-contiguous modified regions. The disclosed systems can further color-code the edited region indicator at an object level based on objects in the modified version of the digital image.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for removing objects from an image stream at capture time of a digital image. For example, the disclosed system contemporaneously detects and segments objects from a digital image stream being previewed in a camera viewfinder graphical user interface of a client device. The disclosed system removes selected objects from the image stream and fills a hole left by the removed object with a content aware fill. Moreover, the disclosed system displays the image stream with the removed object and content fill as the image stream is previewed by a user prior to capturing a digital image from the image stream.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that utilize simultaneous, multi-mesh deformation to implement edge aware transformations of digital images. In particular, in one or more embodiments, the disclosed systems generates a transformation handle that targets an edge portrayed in a digital image. In some cases, the disclosed systems provide the transformation handle for display over the digital image. Additionally, in one or more embodiments, the disclosed systems generate vectors splines and meshes for the edge and one or more influenced regions adjacent to the edge. In response to detecting a user interaction with the transformation handle, the disclosed systems can modify the edge and the at least one influenced region by modifying the corresponding vector splines and meshes.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for implementing part-level semantic aware transformations when editing digital images. For example, the disclosed systems identify a user selection designating an active region of a subpart (e.g., an object portion) to modify in a shape-constrained manner. Additionally, in certain implementations, the disclosed systems identify another user selection to designate an influenced region comprising adjoining areas connected to the active region. In some embodiments, the disclosed systems generate a boundary vector path outlining the active region and the influenced region. Furthermore, the disclosed systems can determine transformation constraints corresponding to specific path segments of the boundary vector path.

Abstract: Methods, systems, and non-transitory computer readable media are disclosed for automatically, accurately, and efficiently correcting eye region artifacts including dark eye regions and wrinkles within a digital image portraying a human face. In particular, in one or more embodiments the disclosed systems localize areas within a digital image to identify eye region artifacts including dark eye regions and wrinkles. In one or more embodiments, the disclosed systems generate a corrected color image by correcting dark eye regions in a low frequency layer of the digital image by replacing the dark eye regions with candidate eye regions. Furthermore, in one or more embodiments the disclosed systems generate a corrected texture image by correcting wrinkles in a high frequency layer by processing the digital image utilizing a smoothing algorithm. The disclosed systems further generate a corrected digital image by combining the corrected color image and the corrected texture image.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for implementing part-level semantic aware transformations when editing digital images. For example, the disclosed systems identify a user selection designating an active region of a subpart (e.g., an object portion) to modify in a shape-constrained manner. Additionally, in certain implementations, the disclosed systems identify another user selection to designate an influenced region comprising adjoining areas connected to the active region. In some embodiments, the disclosed systems generate a boundary vector path outlining the active region and the influenced region. Furthermore, the disclosed systems can determine transformation constraints corresponding to specific path segments of the boundary vector path.

Abstract: Methods and systems are provided for facilitating automated braces removal from individuals in images. In embodiments described herein, an indication to remove the braces from an individual wearing braces in an image is obtained. Based on receiving the indication to remove the braces, automatically, without user intervention, a teeth region is identified in the image that includes teeth of the individual, and a braces region is identified that includes braces visible in the teeth region. The teeth region and braces region are used to generate an edited image that includes the individual without braces.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that utilize simultaneous, multi-mesh deformation to implement edge aware transformations of digital images. In particular, in one or more embodiments, the disclosed systems generates a transformation handle that targets an edge portrayed in a digital image. In some cases, the disclosed systems provide the transformation handle for display over the digital image. Additionally, in one or more embodiments, the disclosed systems generate vectors splines and meshes for the edge and one or more influenced regions adjacent to the edge. In response to detecting a user interaction with the transformation handle, the disclosed systems can modify the edge and the at least one influenced region by modifying the corresponding vector splines and meshes.

Abstract: Methods, systems, and non-transitory computer readable media are disclosed for automatically, accurately, and efficiently correcting eye region artifacts including dark eye regions and wrinkles within a digital image portraying a human face. In particular, in one or more embodiments the disclosed systems localize areas within a digital image to identify eye region artifacts including dark eye regions and wrinkles. In one or more embodiments, the disclosed systems generate a corrected color image by correcting dark eye regions in a low frequency layer of the digital image by replacing the dark eye regions with candidate eye regions. Furthermore, in one or more embodiments the disclosed systems generate a corrected texture image by correcting wrinkles in a high frequency layer by processing the digital image utilizing a smoothing algorithm. The disclosed systems further generate a corrected digital image by combining the corrected color image and the corrected texture image.

Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods for detecting and indicating modifications between a digital image and a modified version of a digital image. For example, the disclosed systems generates an ordered collection of change records in response to detecting modifications to the digital image. The disclosed systems generates determine one or more non-contiguous modified regions of pixels in the digital image based on the change records. The disclosed system generate an edited region indicator corresponding to the non-contiguous modified regions. The disclosed systems can further color-code the edited region indicator at an object level based on objects in the modified version of the digital image.

Abstract: Methods and systems are provided for facilitating automated braces removal from individuals in images. In embodiments described herein, an indication to remove the braces from an individual wearing braces in an image is obtained. Based on receiving the indication to remove the braces, automatically, without user intervention, a teeth region is identified in the image that includes teeth of the individual, and a braces region is identified that includes braces visible in the teeth region. The teeth region and braces region are used to generate an edited image that includes the individual without braces.

Abstract: Methods, systems, and non-transitory computer readable media are disclosed for generating a modified vector drawing based on user input in a magnified view. The disclosed system presents a vector drawing comprising anchor points in a drawing view. In one or more embodiments, the disclosed system determines that a user interaction (e.g., a user touch gesture) with the vector drawing results in an ambiguous selection of two or more anchor points. Based on this determination, the disclosed system can determine a magnification level for a magnified view in which the two or more anchor points are spaced at least a touch diameter. The disclosed system may receive a selection of an anchor point in the magnified view and user input indicating an operation to be performed on the selected anchor point. The disclosed system can generate a modified vector drawing by performing the operation.

Abstract: Techniques for automatically synchronizing poses of objects in an image or between multiple images. An automatic pose synchronization functionality is provided by an image editor. The image editor identifies or enables a user to select objects (e.g., people) whose poses are to be synchronized and the image editor then performs processing to automatically synchronize the poses of the identified objects. For two objects whose poses are to be synchronized, a reference object is identified as one whose associated pose is to be used as a reference pose. A target object is identified as one whose associated pose is to be modified to match the reference pose of the reference object. An output image is generated by the image editor in which the position of a part of the target object is modified such that the pose associated with the target object matches the reference pose of the reference object.

Abstract: Techniques for automatically synchronizing poses of objects in an image or between multiple images. An automatic pose synchronization functionality is provided by an image editor. The image editor identifies or enables a user to select objects (e.g., people) whose poses are to be synchronized and the image editor then performs processing to automatically synchronize the poses of the identified objects. For two objects whose poses are to be synchronized, a reference object is identified as one whose associated pose is to be used as a reference pose. A target object is identified as one whose associated pose is to be modified to match the reference pose of the reference object. An output image is generated by the image editor in which the position of a part of the target object is modified such that the pose associated with the target object matches the reference pose of the reference object.

Abstract: Object tracking verification techniques are described as implemented by a computing device. In one example, feature points are selected on and along a boundary of an object to be tracked, e.g., in an initial frame of a digital video, which are referred to as “feature points.” Tracking of the feature points is verified by the computing device between frames. If the feature points have been found to deviate from the object, the feature points are reselected. To verify the feature points, a number of tracked features points in a subsequent frame is compared to a number of feature points used to initiate tracking with respect to a threshold. Based on this comparison, if a number of feature points is “lost” in the subsequent frame that is greater than the threshold, the feature points are reselected for tracking the object in subsequent frames of the video.