Patents by Inventor Baldo Faieta

Baldo Faieta has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20220415084
    Abstract: Embodiments are disclosed for finding similar persons in images. In particular, in one or more embodiments, the disclosed systems and methods comprise receiving an image query, the image query including an input image that includes a representation of a person, generating a first cropped image including a representation of the person's face and a second cropped image including a representation of the person's body, generating an image embedding for the input image by combining a face embedding corresponding to the first cropped image and a body embedding corresponding to the second cropped image, and querying an image repository in embedding space by comparing the image embedding to a plurality of image embeddings associated with a plurality of images in the image repository to obtain one or more images based on similarity to the input image in the embedding space.
    Type: Application
    Filed: September 2, 2022
    Publication date: December 29, 2022
    Applicant: Adobe Inc.
    Inventors: Saeid MOTIIAN, Zhe LIN, Shabnam GHADAR, Baldo FAIETA
  • Patent number: 11531697
    Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately, efficiently, and flexibly identifying and providing digital images of human figures in poses corresponding to a query pose. In particular, the disclosed systems can provide multiple approaches to searching for and providing pose images, including identifying a digital image depicting a human figure in a particular pose based on a query digital image that depicts the pose or identifying a digital image depicting a human figure in a particular pose based on a virtual mannequin. Indeed, the disclosed systems can provide a manipulable virtual mannequin that defines a query pose for searching a repository of digital images. Additionally, the disclosed systems can generate and provide digital pose image groups by clustering digital images together according to poses of human figures within a pose feature space.
    Type: Grant
    Filed: November 3, 2020
    Date of Patent: December 20, 2022
    Assignee: Adobe Inc.
    Inventors: Jinrong Xie, Shabnam Ghadar, Jun Saito, Jimei Yang, Elnaz Morad, Duygu Ceylan Aksit, Baldo Faieta, Alex Filipkowski
  • Publication number: 20220391633
    Abstract: Methods, systems, and non-transitory computer readable media are disclosed for accurately and efficiently generating groups of images portraying semantically similar objects for utilization in building machine learning models. In particular, the disclosed system utilizes metadata and spatial statistics to extract semantically similar objects from a repository of digital images. In some embodiments, the disclosed system generates color embeddings and content embeddings for the identified objects. The disclosed system can further group similar objects together within a query space by utilizing a clustering algorithm to create object clusters and then refining and combining the object clusters within the query space. In some embodiments, the disclosed system utilizes one or more of the object clusters to build a machine learning model.
    Type: Application
    Filed: June 2, 2021
    Publication date: December 8, 2022
    Inventors: Midhun Harikumar, Zhe Lin, Shabnam Ghadar, Baldo Faieta
  • Publication number: 20220391611
    Abstract: Systems and methods for image processing are described. One or more embodiments of the present disclosure identify a latent vector representing an image of a face, identify a target attribute vector representing a target attribute for the image, generate a modified latent vector using a mapping network that converts the latent vector and the target attribute vector into a hidden representation having fewer dimensions than the latent vector, wherein the modified latent vector is generated based on the hidden representation, and generate a modified image based on the modified latent vector, wherein the modified image represents the face with the target attribute.
    Type: Application
    Filed: June 8, 2021
    Publication date: December 8, 2022
    Inventors: RATHEESH KALAROT, Siavash Khodadadeh, Baldo Faieta, Shabnam Ghadar, Saeid Motiian, Wei-An Lin, Zhe Lin
  • Publication number: 20220300729
    Abstract: Embodiments are disclosed for finding similar persons in images. In particular, in one or more embodiments, the disclosed systems and methods comprise receiving an image query, the image query including an input image that includes a representation of a person, generating a first cropped image including a representation of the person's face and a second cropped image including a representation of the person's body, generating an image embedding for the input image by combining a face embedding corresponding to the first cropped image and a body embedding corresponding to the second cropped image, and querying an image repository in embedding space by comparing the image embedding to a plurality of image embeddings associated with a plurality of images in the image repository to obtain one or more images based on similarity to the input image in the embedding space.
    Type: Application
    Filed: March 19, 2021
    Publication date: September 22, 2022
    Inventors: Saeid MOTIIAN, Zhe LIN, Shabnam GHADAR, Baldo FAIETA
  • Publication number: 20220284321
    Abstract: Systems and methods for multi-modal representation learning are described. One or more embodiments provide a visual representation learning system trained using machine learning techniques. For example, some embodiments of the visual representation learning system are trained using cross-modal training tasks including a combination of intra-modal and inter-modal similarity preservation objectives. In some examples, the training tasks are based on contrastive learning techniques.
    Type: Application
    Filed: March 3, 2021
    Publication date: September 8, 2022
    Inventors: Xin Yuan, Zhe Lin, Jason Wen Yong Kuen, Jianming Zhang, Yilin Wang, Ajinkya Kale, Baldo Faieta
  • Patent number: 11436865
    Abstract: Embodiments are disclosed for finding similar persons in images. In particular, in one or more embodiments, the disclosed systems and methods comprise receiving an image query, the image query including an input image that includes a representation of a person, generating a first cropped image including a representation of the person's face and a second cropped image including a representation of the person's body, generating an image embedding for the input image by combining a face embedding corresponding to the first cropped image and a body embedding corresponding to the second cropped image, and querying an image repository in embedding space by comparing the image embedding to a plurality of image embeddings associated with a plurality of images in the image repository to obtain one or more images based on similarity to the input image in the embedding space.
    Type: Grant
    Filed: March 19, 2021
    Date of Patent: September 6, 2022
    Assignee: Adobe Inc.
    Inventors: Saeid Motiian, Zhe Lin, Shabnam Ghadar, Baldo Faieta
  • Publication number: 20220277039
    Abstract: The present disclosure describes systems and methods for information retrieval. Embodiments of the disclosure provide a color embedding network trained using machine learning techniques to generate embedded color representations for color terms included in a text search query. For example, techniques described herein are used to represent color text in a same space as color embeddings (e.g., an embedding space created by determining a histogram of LAB based colors in a three-dimensional (3D) space). Further, techniques are described for indexing color palettes for all the searchable images in the search space. Accordingly, color terms in a text query are directly converted into a color palette and an image search system can return one or more search images with corresponding color palettes that are relevant to (e.g., within a threshold distance from) the color palette of the text query.
    Type: Application
    Filed: February 26, 2021
    Publication date: September 1, 2022
    Inventors: PRANAV AGGARWAL, Ajinkya Kale, Baldo Faieta, Saeid Motiian, Venkata naveen kumar yadav Marri
  • Publication number: 20220270310
    Abstract: The present disclosure describes systems, methods, and non-transitory computer readable media for detecting user interactions to edit a digital image from a client device and modify the digital image for the client device by using a web-based intermediary that modifies a latent vector of the digital image and an image modification neural network to generate a modified digital image from the modified latent vector. In response to user interaction to modify a digital image, for instance, the disclosed systems modify a latent vector extracted from the digital image to reflect the requested modification. The disclosed systems further use a latent vector stream renderer (as an intermediary device) to generate an image delta that indicates a difference between the digital image and the modified digital image. The disclosed systems then provide the image delta as part of a digital stream to a client device to quickly render the modified digital image.
    Type: Application
    Filed: February 23, 2021
    Publication date: August 25, 2022
    Inventors: Akhilesh Kumar, Baldo Faieta, Piotr Walczyszyn, Ratheesh Kalarot, Archie Bagnall, Shabnam Ghadar, Wei-An Lin, Cameron Smith, Christian Cantrell, Patrick Hebron, Wilson Chan, Jingwan Lu, Holger Winnemoeller, Sven Olsen
  • Publication number: 20220253990
    Abstract: The present disclosure describes systems and methods for image enhancement. Embodiments of the present disclosure provide an image enhancement system with a feedback mechanism that provides quantifiable image enhancement information. An image enhancement system may include a discriminator network that determines the quality of the media object. In cases where the discriminator network determines that the media object has a low image quality score (e.g., an image quality score below a quality threshold), the image enhancement system may perform enhancement on the media object using an enhancement network (e.g., using an enhancement network that includes a generative neural network or a generative adversarial network (GAN) model). The discriminator network may then generate an enhancement score for the enhanced media object that may be provided to the user as a feedback mechanism (e.g.
    Type: Application
    Filed: February 10, 2021
    Publication date: August 11, 2022
    Inventors: Akhilesh Kumar, Zhe Lin, Baldo Faieta
  • Publication number: 20220237830
    Abstract: Embodiments are disclosed for automatic object re-colorization in images.
    Type: Application
    Filed: January 22, 2021
    Publication date: July 28, 2022
    Inventors: Siavash KHODADADEH, Zhe LIN, Shabnam GHADAR, Saeid MOTIIAN, Richard ZHANG, Ratheesh KALAROT, Baldo FAIETA
  • Patent number: 11380033
    Abstract: Based on a received digital image and text, a neural network trained to identify candidate text placement areas within images may be used to generate a mask for the digital image that includes a candidate text placement area. A bounding box for the digital image may be defined for the text and based on the candidate text placement area, and the text may be superimposed onto the digital image within the bounding box.
    Type: Grant
    Filed: January 9, 2020
    Date of Patent: July 5, 2022
    Assignee: ADOBE INC.
    Inventors: Kate Sousa, Zhe Lin, Saeid Motiian, Pramod Srinivasan, Baldo Faieta, Alex Filipkowski
  • Patent number: 11367273
    Abstract: The present disclosure is directed toward systems and methods for detecting an object in an input image based on a target object keyword. For example, one or more embodiments described herein generate a heat map of the input image based on the target object keyword and generate various bounding boxes based on a pixel analysis of the heat map. One or more embodiments described herein then utilize the various bounding boxes to determine scores for generated object location proposals in order to provide a highest scoring object location proposal overlaid on the input image.
    Type: Grant
    Filed: July 2, 2020
    Date of Patent: June 21, 2022
    Assignee: Adobe Inc.
    Inventors: Delun Du, Zhe Lin, Baldo Faieta
  • Patent number: 11361018
    Abstract: Systems and methods for searching digital content are disclosed. A method includes receiving, from a user, a base search constraint. A search constraint includes search values or criteria. A recall set is generated based on the base search constraint. Recommended search constraints are determined and provided to the user. The recommended search constraints are statistically associated with the base search constraint. The method receives, from the user, a selection of a first search constraint included in the plurality of recommend search constraints. The method generates and provides search results to the user that include a re-ordering of the recall set. The re-ordering is based on a search constraint set that includes both the base search constraint and the selected first search constraint. The re-ordering is further based on a weight associated with the base search constraint and another user-provided weight associated with the first search constraint.
    Type: Grant
    Filed: November 28, 2017
    Date of Patent: June 14, 2022
    Assignee: Adobe Inc.
    Inventors: Samarth Gulati, Brett Michael Butterfield, Baldo Faieta, Kent Andrew Edmonds
  • Publication number: 20220164380
    Abstract: A query image is received, along with a query to initiate a search process to find other images based on the query image. The query includes a preference value associated with an attribute, the preference value indicative of a level of emphasis to be placed on the attribute during the search. A full query vector, which is within a first dimensional space and representative of the query image, is generated. The full query vector is projected to a reduced dimensional space having a dimensionality lower than the first dimensional space, to generate a query vector. An attribute direction corresponding to the attribute is identified. A plurality of candidate vectors of the reduced dimensional space is searched, based on the attribute direction, the query vector, and the preference value, to identify a target vector of the plurality of candidate vectors. A target image, representative of the target vector, is displayed.
    Type: Application
    Filed: November 25, 2020
    Publication date: May 26, 2022
    Applicant: Adobe Inc.
    Inventors: Zhe Lin, Shabnam Ghadar, Saeid Motiian, Ratheesh Kalarot, Baldo Faieta, Alireza Zaeemzadeh
  • Publication number: 20220156992
    Abstract: A non-transitory computer-readable medium includes program code that is stored thereon. The program code is executable by one or more processing devices for performing operations including generating, by a model that includes trainable components, a learned image representation of a target image. The operations further include generating, by a text embedding model, a text embedding of a text query. The text embedding and the learned image representation of the target image are in a same embedding space. Additionally, the operations include generating a class activation map of the target image by, at least, convolving the learned image representation of the target image with the text embedding of the text query. Moreover, the operations include generating an object-segmented image using the class activation map of the target image.
    Type: Application
    Filed: November 18, 2020
    Publication date: May 19, 2022
    Inventors: Midhun Harikumar, Pranav Aggarwal, Baldo Faieta, Ajinkya Kale, Zhe Lin
  • Publication number: 20220138249
    Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately, efficiently, and flexibly identifying and providing digital images of human figures in poses corresponding to a query pose. In particular, the disclosed systems can provide multiple approaches to searching for and providing pose images, including identifying a digital image depicting a human figure in a particular pose based on a query digital image that depicts the pose or identifying a digital image depicting a human figure in a particular pose based on a virtual mannequin. Indeed, the disclosed systems can provide a manipulable virtual mannequin that defines a query pose for searching a repository of digital images. Additionally, the disclosed systems can generate and provide digital pose image groups by clustering digital images together according to poses of human figures within a pose feature space.
    Type: Application
    Filed: November 3, 2020
    Publication date: May 5, 2022
    Inventors: Jinrong Xie, Shabnam Ghadar, Jun Saito, Jimei Yang, Elnaz Morad, Duygu Ceylan Aksit, Baldo Faieta, Alex Filipkowski
  • Publication number: 20220138247
    Abstract: Embodiments of the technology described herein, provide improved visual search results by combining a visual similarity and a textual similarity between images. In an embodiment, the visual similarity is quantified as a visual similarity score and the textual similarity is quantified as a textual similarity score. The textual similarity is determined based on text, such as a title, associated with the image. The overall similarity of two images is quantified as a weighted combination of the textual similarity score and the visual similarity score. In an embodiment, the weighting between the textual similarity score and the visual similarity score is user configurable through a control on the search interface. In one embodiment, the aggregate similarity score is the sum of a weighted visual similarity score and a weighted textual similarity score.
    Type: Application
    Filed: November 5, 2020
    Publication date: May 5, 2022
    Inventors: Mikhail Kotov, Roland Geisler, Saeid Motiian, Dylan Nathaniel Warnock, Michele Saad, Venkata Naveen Kumar Yadav Marri, Ajinkya Kale, Ryan Rozich, Baldo Faieta
  • Publication number: 20220121931
    Abstract: Systems and methods train and apply a specialized encoder neural network for fast and accurate projection into the latent space of a Generative Adversarial Network (GAN). The specialized encoder neural network includes an input layer, a feature extraction layer, and a bottleneck layer positioned after the feature extraction layer. The projection process includes providing an input image to the encoder and producing, by the encoder, a latent space representation of the input image. Producing the latent space representation includes extracting a feature vector from the feature extraction layer, providing the feature vector to the bottleneck layer as input, and producing the latent space representation as output. The latent space representation produced by the encoder is provided as input to the GAN, which generates an output image based upon the latent space representation. The encoder is trained using specialized loss functions including a segmentation loss and a mean latent loss.
    Type: Application
    Filed: July 23, 2021
    Publication date: April 21, 2022
    Inventors: Ratheesh Kalarot, Wei-An Lin, Cameron Smith, Zhixin Shu, Baldo Faieta, Shabnam Ghadar, Jingwan Lu, Aliakbar Darabi, Jun-Yan Zhu, Niloy Mitra, Richard Zhang, Elya Shechtman
  • Publication number: 20220122306
    Abstract: Systems and methods dynamically adjust an available range for editing an attribute in an image. An image editing system computes a metric for an attribute in an input image as a function of a latent space representation of the input image and a filtering vector for editing the input image. The image editing system compares the metric to a threshold. If the metric exceeds the threshold, then the image editing system selects a first range for editing the attribute in the input image. If the metric does not exceed the threshold, a second range is selected. The image editing system causes display of a user interface for editing the input image comprising an interface element for editing the attribute within the selected range.
    Type: Application
    Filed: September 7, 2021
    Publication date: April 21, 2022
    Inventors: Wei-An Lin, Baldo Faieta, Cameron Smith, Elya Shechtman, Jingwan Lu, Jun-Yan Zhu, Niloy Mitra, Ratheesh Kalarot, Richard Zhang, Shabnam Ghadar, Zhixin Shu