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公开(公告)号：US20210256775A1
公开(公告)日：2021-08-19
申请号：US17208627
申请日：2021-03-22
Applicant: ADOBE INC.
Inventor： Duygu Ceylan Aksit , Vladimir Kim , Siddhartha Chaudhuri , Radomir Mech , Noam Aigerman , Kevin Wampler , Jonathan Eisenmann , Giorgio Gori , Emiliano Gambaretto
IPC: G06T19/20
Abstract: Embodiments of the present invention are directed towards intuitive editing of three-dimensional models. In embodiments, salient geometric features associated with a three-dimensional model defining an object are identified. Thereafter, feature attributes associated with the salient geometric features are identified. A feature set including a plurality of salient geometric features related to one another is generated based on the determined feature attributes (e.g., properties, relationships, distances). An editing handle can then be generated and displayed for the feature set enabling each of the salient geometric features within the feature set to be edited in accordance with a manipulation of the editing handle. The editing handle can be displayed in association with one of the salient geometric features of the feature set.
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公开(公告)号：US10977549B2
公开(公告)日：2021-04-13
申请号：US16276559
申请日：2019-02-14
Applicant: Adobe Inc.
Inventor： Vladimir Kim , Omid Poursaeed , Jun Saito , Elya Shechtman
Abstract: In implementations of object animation using generative neural networks, one or more computing devices of a system implement an animation system for reproducing animation of an object in a digital video. A mesh of the object is obtained from a first frame of the digital video and a second frame of the digital video having the object is selected. Features of the object from the second frame are mapped to vertices of the mesh, and the mesh is warped based on the mapping. The warped mesh is rendered as an image by a neural renderer and compared to the object from the second frame to train a neural network. The rendered image is then refined by a generator of a generative adversarial network which includes a discriminator. The discriminator trains the generator to reproduce the object from the second frame as the refined image.
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13.发明授权公开(公告)号：US10521970B2
公开(公告)日：2019-12-31
申请号：US15900864
申请日：2018-02-21
Applicant: Adobe Inc.
Inventor： Emiliano Gambaretto , Vladimir Kim , Qingnan Zhou , Mehmet Ersin Yumer
Abstract: Certain embodiments involve refining local parameterizations that apply two-dimensional (“2D”) images to three-dimensional (“3D”) models. For instance, a particular parameterization-initialization process is select based on one or more features of a target mesh region. An initial local parameterization for a 2D image is generated from this parameterization-initialization process. A quality metric for the initial local parameterization is computed, and the local parameterization is modified to improve the quality metric. The 3D model is modified by applying image points from the 2D image to the target mesh region in accordance with the modified local parameterization.
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公开(公告)号：US10204423B2
公开(公告)日：2019-02-12
申请号：US15430659
申请日：2017-02-13
Applicant: Adobe Inc.
Inventor： Vladimir Kim , Oliver Wang , Minhyuk Sung , Mehmet Ersin Yumer
Abstract: Disclosed are techniques for more accurately estimating the pose of a camera used to capture a three-dimensional scene. Accuracy is enhanced by leveraging three-dimensional object priors extracted from a large-scale three-dimensional shape database. This allows existing feature matching techniques to be augmented by generic three-dimensional object priors, thereby providing robust information about object orientations across multiple images or frames. More specifically, the three-dimensional object priors provide a unit that is easier and more reliably tracked between images than a single feature point. By adding object pose estimates across images, drift is reduced and the resulting visual odometry techniques are more robust and accurate. This eliminates the need for three-dimensional object templates that are specifically generated for the imaged object, training data obtained for a specific environment, and other tedious preprocessing steps. Entire object classes identified in a three-dimensional shape database can be used to train an object detector.
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公开(公告)号：US20250078408A1
公开(公告)日：2025-03-06
申请号：US18458032
申请日：2023-08-29
Applicant: Adobe Inc.
Inventor： Valentin Mathieu Deschaintre , Vladimir Kim , Thibault Groueix , Julien Philip
IPC: G06T17/20 , G06T7/40 , H04N13/279
Abstract: Implementations of systems and methods for determining viewpoints suitable for performing one or more digital operations on a three-dimensional object are disclosed. Accordingly, a set of candidate viewpoints is established. The subset of candidate viewpoints provides views of an outer surface of a three-dimensional object and those views provide overlapping surface data. A subset of activated viewpoints is determined from the set of candidate viewpoints, the subset of activated viewpoints providing less of the overlapping surface data. The subset of activated viewpoints is used to perform one or more digital operation on the three-dimensional object.
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Patent Agency Ranking
16.发明授权公开(公告)号：US11257298B2
公开(公告)日：2022-02-22
申请号：US16822819
申请日：2020-03-18
Applicant: Adobe Inc.
Inventor： Vladimir Kim , Pierre-alain Langlois , Oliver Wang , Matthew Fisher , Bryan Russell
Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for reconstructing three-dimensional meshes from two-dimensional images of objects with automatic coordinate system alignment. For example, the disclosed system can generate feature vectors for a plurality of images having different views of an object. The disclosed system can process the feature vectors to generate coordinate-aligned feature vectors aligned with a coordinate system associated with an image. The disclosed system can generate a combined feature vector from the feature vectors aligned to the coordinate system. Additionally, the disclosed system can then generate a three-dimensional mesh representing the object from the combined feature vector.
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公开(公告)号：US11189094B2
公开(公告)日：2021-11-30
申请号：US16985402
申请日：2020-08-05
Applicant: Adobe, Inc.
Inventor： Oliver Wang , Vladimir Kim , Matthew Fisher , Elya Shechtman , Chen-Hsuan Lin , Bryan Russell
Abstract: Techniques are disclosed for 3D object reconstruction using photometric mesh representations. A decoder is pretrained to transform points sampled from 2D patches of representative objects into 3D polygonal meshes. An image frame of the object is fed into an encoder to get an initial latent code vector. For each frame and camera pair from the sequence, a polygonal mesh is rendered at the given viewpoints. The mesh is optimized by creating a virtual viewpoint, rasterized to obtain a depth map. The 3D mesh projections are aligned by projecting the coordinates corresponding to the polygonal face vertices of the rasterized mesh to both selected viewpoints. The photometric error is determined from RGB pixel intensities sampled from both frames. Gradients from the photometric error are backpropagated into the vertices of the assigned polygonal indices by relating the barycentric coordinates of each image to update the latent code vector.
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公开(公告)号：US20210294834A1
公开(公告)日：2021-09-23
申请号：US16821301
申请日：2020-03-17
Applicant: ADOBE INC.
Inventor： Long Mai , Michael Alcorn , Baldo Faieta , Vladimir Kim
Abstract: Systems and methods for performing image search are described. An image search method may include generating a feature vector for each of a plurality of stored images using a machine learning model trained using a rotation loss term, receiving a search query comprising a search image with object having an orientation, generating a query feature vector for the search image using the machine learning model, wherein the query feature vector is based at least in part on the orientation, comparing the query feature vector to the feature vector for each of the plurality of stored images, and selecting at least one stored image of the plurality of stored images based on the comparison, wherein the at least one stored image comprises a similar orientation to the orientation of the object in the search image.
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公开(公告)号：US11106902B2
公开(公告)日：2021-08-31
申请号：US15920027
申请日：2018-03-13
Applicant: Adobe Inc.
Inventor： Zimo Li , Vladimir Kim , Mehmet Ersin Yumer
Abstract: Certain embodiments detect human-object interactions in image content. For example, human-object interaction metadata is applied to an input image, thereby identifying contact between a part of a depicted human and a part of a depicted object. Applying the human-object interaction metadata involves computing a joint-location heat map by applying a pose estimation subnet to the input image and a contact-point heat map by applying an object contact subnet to the to the input image. The human-object interaction metadata is generated by applying an interaction-detection subnet to the joint-location heat map and the contact-point heat map. The interaction-detection subnet is trained to identify an interaction based on joint-object contact pairs, where a joint-object contact pair includes a relationship between a human joint location and a contact point. An image search system or other computing system is provided with access to the input image having the human-object interaction metadata.
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公开(公告)号：US20200265294A1
公开(公告)日：2020-08-20
申请号：US16276559
申请日：2019-02-14
Applicant: Adobe Inc.
Inventor： Vladimir Kim , Omid Poursaeed , Jun Saito , Elya Shechtman
Abstract: In implementations of object animation using generative neural networks, one or more computing devices of a system implement an animation system for reproducing animation of an object in a digital video. A mesh of the object is obtained from a first frame of the digital video and a second frame of the digital video having the object is selected. Features of the object from the second frame are mapped to vertices of the mesh, and the mesh is warped based on the mapping. The warped mesh is rendered as an image by a neural renderer and compared to the object from the second frame to train a neural network. The rendered image is then refined by a generator of a generative adversarial network which includes a discriminator. The discriminator trains the generator to reproduce the object from the second frame as the refined image.
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