Adobe, Inc.

Other

Czech Technical University in Prague

Jakub Fiser

Paul John Asente

Jingwan Lu

Elya Shechtman

Ondrej Jamriska

Daniel Sýkora

David P Simons

Stephen N Schiller

Michal Lukác

Michal Lukac

Baldo Antonio Faieta

Vineet Batra

Ankit Phogat

Shabnam Ghadar

Yang Yang

Geoffrey Heller

Zhixin Shu

Cameron Smith

Alex Charles Filipkowski

Elya Schechtman

Face anonymization techniques are described that overcome conventional challenges to generate an anonymized face. In one example, a digital object editing system is configured to generate an anonymized face based on a target face and a reference face. As part of this, the digital object editing system employs an encoder as part of machine learning to extract a target encoding of the target face image and a reference encoding of the reference face. The digital object editing system then generates a mixed encoding from the target and reference encodings. The mixed encoding is employed by a machine-learning model of the digital object editing system to generate a mixed face. An object replacement module is used by the digital object editing system to replace the target face in the target digital image with the mixed face.

Face anonymization in digital images

Methods, systems, and non-transitory computer readable storage media are disclosed for utilizing ray-tracing and mesh generation to illuminate two-dimensional digital vector images. In response to inserting a light source into a two-dimensional digital vector image including one or more vector elements, the disclosed system embeds the vector element(s) into a polygonal mesh generated for a region of the digital vector image. The disclosed system samples a plurality of rays at a plurality of points within the region and detect intersections of the rays with the vector element(s) or a bounding shape surrounding the region. Additionally, the disclosed system determines color values for mesh points in the polygonal mesh based on the intersections of the rays by interpolating color values associated with the intersected points. Furthermore, in some embodiments, the disclosed system subdivides the polygonal mesh according to a priority queue based on error scores associated with the determined color values.

Generating illuminated two-dimensional vector graphics using path tracing

Freeform drawing beautification techniques are described. An input is received by a computing device describing a freeform path drawn by a user as part of a drawing, the freeform path not formed solely as a circular arc or a circle (e.g., a fixed distance from a point) and including one or more curved elements. The drawing is examined by the computing device to locate another curved element in the drawing. One or more suggestions are constructed to adjust the freeform path by the computing device based on the located curved element in the drawing. The constructed one or more suggestions are output to adjust the freeform path by the computing device.

Freeform drawing beautification

Certain embodiments involve automatically detecting video frames that depict visemes and that are usable for generating an animatable puppet. For example, a computing device accesses video frames depicting a person performing gestures usable for generating a layered puppet, including a viseme gesture corresponding to a target sound or phoneme. The computing device determines that audio data including the target sound or phoneme aligns with a particular video frame from the video frames that depicts the person performing the viseme gesture. The computing device creates, from the video frames, a puppet animation of the gestures, including an animation of the viseme corresponding to the target sound or phoneme that is generated from the particular video frame. The computing device outputs the puppet animation to a presentation device.

Automatic viseme detection for generating animatable puppet

Certain embodiments involve generating one or more of appearance guide and a positional guide and using one or more of the guides to synthesize a stylized image or animation. For example, a system obtains data indicating a target image and a style exemplar image. The system generates an appearance guide, a positional guide, or both from the target image and the style exemplar image. The system uses one or more of the guides to transfer a texture or style from the style exemplar image to the target image.

Generating a stylized image or stylized animation by matching semantic features via an appearance guide, a segmentation guide, and/or a temporal guide

Embodiments of the present invention are directed to beautifying freeform input paths in accordance with paths existing in the drawing (i.e., resolved paths). In some embodiments of the present invention, freeform input paths of a curved format can be modified or replaced to more precisely illustrate a path desired by a user. As such, a user can provide a freeform input path that resembles a path of interest by the user, but is not as precise as desired. Based on existing paths in the electronic drawing, a path suggestion(s) can be generated to rectify, modify, or replace the input path with a more precise path. In some cases, a user can then select a desired path suggestion, and the selected path then replaces the initially provided freeform input path.

Beautifying freeform drawings using arc and circle center snapping

Beautifying freeform drawings using transformation adjustments

Certain embodiments involve generating an appearance guide, a segmentation guide, and a positional guide and using one or more of the guides to synthesize a stylized image or animation. For example, a system obtains data indicating a target and a style exemplar image and generates a segmentation guide for segmenting the target image and the style exemplar image and identifying a feature of the target image and a corresponding feature of the style exemplar image. The system generates a positional guide for determining positions of the target feature and style feature relative to a common grid system. The system generates an appearance guide for modifying intensity levels and contrast values in the target image based on the style exemplar image. The system uses one or more of the guides to transfer a texture of the style feature to the corresponding target feature.

Certain embodiments involve automatically generating a layered animatable puppet using a content stream. For example, a system identifies various frames of a content stream that includes a character performing various gestures usable for generating a layered puppet. The system separates the various frames of the content stream into various individual layers. The system extracts a face of the character from the various individual layers and creates the layered puppet by combining the individual layers and using the face of the character. The system can output the layered puppet for animation to perform a gesture of the various gestures.

Generating a layered animatable puppet using a content stream

Techniques for illumination-guided example-based stylization of 3D renderings are described. In implementations, a source image and a target image are obtained, where each image includes a multi-channel image having at least a style channel and multiple light path expression (LPE) channels having light propagation information. Then, the style channel of the target image is synthesized to mimic a stylization of individual illumination effects from the style channel of the source image. As part of the synthesizing, the light propagation information is applied as guidance for synthesis of the style channel of the target image. Based on the guidance, the stylization of individual illumination effects from the style channel of the source image is transferred to the style channel of the target image. Based on the transfer, the style channel of the target image is then generated for display of the target image via a display device.

Illumination-guided example-based stylization of 3D renderings

Beautifying freeform drawings

Techniques for controlling patch-usage in image synthesis are described. In implementations, a curve is fitted to a set of sorted matching errors that correspond to potential source-to-target patch assignments between a source image and a target image. Then, an error budget is determined using the curve. In an example, the error budget is usable to identify feasible patch assignments from the potential source-to-target patch assignments. Using the error budget along with uniform patch-usage enforcement, source patches from the source image are assigned to target patches in the target image. Then, at least one of the assigned source patches is assigned to an additional target patch based on the error budget. Subsequently, an image is synthesized based on the source patches assigned to the target patches.

Controlling patch usage in image synthesis

Appearance transfer techniques are described in the following. In one example, a search and vote process is configured to select patches from the image exemplar and then search for a location in the target image that is a best fit for the patches. As part of this selection, a patch usage counter may also be employed in an example to ensure that selection of each of the patches from the image exemplar does not vary by more than one, one to another. In another example, transfer of an appearance of a boundary and interiors regions from the image exemplar to a target image is preserved.

Appearance transfer techniques

Appearance transfer techniques are described in the following that maintain temporal coherence between frames. In one example, a previous frame of a target video is warped that occurs in the sequence of the target video before a particular frame being synthesized. Color of the particular frame is transferred from an appearance of a corresponding frame of a video exemplar. In a further example, emitter portions are identified and addressed to preserve temporal coherence. This is performed to reduce an influence of the emitter portion of the target region in the selection of patches.

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Prague, Czechia

Jakub Fiser