公开(公告)号：US12093308B2

公开(公告)日：2024-09-17

申请号：US17453595

申请日：2021-11-04

Applicant: ADOBE INC.

Inventor： Baldo Faieta ,  Ajinkya Gorakhnath Kale ,  Pranav Vineet Aggarwal ,  Naveen Marri ,  Saeid Motiian ,  Tracy Holloway King ,  Alex Filipkowski ,  Shabnam Ghadar

IPC: G06F16/583 ,  G06F16/535 ,  G06F16/538 ,  G06F16/58 ,  G06F40/295 ,  G06N3/08

CPC classification number: G06F16/5838 ,  G06F16/535 ,  G06F16/538 ,  G06F16/5866 ,  G06F40/295 ,  G06N3/08

Abstract: Systems and methods for image retrieval are described. Embodiments of the present disclosure receive a search query from a user; extract an entity and a color phrase describing the entity from the search query; generate an entity color embedding in a color embedding space from the color phrase using a multi-modal color encoder; identify an image in a database based on metadata for the image including an object label corresponding to the extracted entity and an object color embedding in the color embedding space corresponding to the object label; and provide image information for the image to the user based on the metadata.

公开(公告)号：US12079269B2

公开(公告)日：2024-09-03

申请号：US18104848

申请日：2023-02-02

Applicant: Adobe Inc.

Inventor： Pranav Vineet Aggarwal ,  Zhe Lin ,  Baldo Antonio Faieta ,  Saeid Antonio Motiian

IPC: G06F16/00 ,  G06F16/538 ,  G06F16/583 ,  G06F18/21 ,  G06F18/22 ,  G06N3/08 ,  G06N20/00 ,  G06V10/82 ,  G06V10/94 ,  G06V30/19 ,  G06V30/262 ,  G06F40/30 ,  G10L15/22

CPC classification number: G06F16/583 ,  G06F16/538 ,  G06F18/21 ,  G06F18/22 ,  G06N3/08 ,  G06N20/00 ,  G06V10/82 ,  G06V10/945 ,  G06V30/19147 ,  G06V30/1916 ,  G06V30/19173 ,  G06V30/274 ,  G06F40/30 ,  G10L15/22

Abstract: Visually guided machine-learning language model and embedding techniques are described that overcome the challenges of conventional techniques in a variety of ways. In one example, a model is trained to support a visually guided machine-learning embedding space that supports visual intuition as to “what” is represented by text. The visually guided language embedding space supported by the model, once trained, may then be used to support visual intuition as part of a variety of functionality. In one such example, the visually guided language embedding space as implemented by the model may be leveraged as part of a multi-modal differential search to support search of digital images and other digital content with real-time focus adaptation which overcomes the challenges of conventional techniques.

公开(公告)号：US11775578B2

公开(公告)日：2023-10-03

申请号：US17398317

申请日：2021-08-10

Applicant: Adobe Inc.

Inventor： Pranav Vineet Aggarwal ,  Zhe Lin ,  Baldo Antonio Faieta ,  Saeid Motiian

IPC: G06K9/62 ,  G06K9/72 ,  G06F16/535 ,  G06N20/00 ,  G06V30/262 ,  G06F18/40 ,  G06F18/214 ,  G06V30/19 ,  G06V10/82 ,  G06V10/94 ,  G06F3/0482

CPC classification number: G06F16/535 ,  G06F18/2148 ,  G06F18/40 ,  G06N20/00 ,  G06V10/82 ,  G06V10/945 ,  G06V30/1916 ,  G06V30/19147 ,  G06V30/19173 ,  G06V30/274 ,  G06F3/0482

Abstract: Text-to-visual machine learning embedding techniques are described that overcome the challenges of conventional techniques in a variety of ways. These techniques include use of query-based training data which may expand availability and types of training data usable to train a model. Generation of negative digital image samples is also described that may increase accuracy in training the model using machine learning. A loss function is also described that also supports increased accuracy and computational efficiency by losses separately, e.g., between positive or negative sample embeddings a text embedding.

公开(公告)号：US20230298224A1

公开(公告)日：2023-09-21

申请号：US17655035

申请日：2022-03-16

Applicant: ADOBE INC.

Inventor： Pranav Vineet Aggarwal ,  Midhun Harikumar ,  Ajinkya Gorakhnath Kale

IPC: G06T11/00 ,  G06T11/80 ,  G06F16/583 ,  G06N3/04 ,  G06F16/538

CPC classification number: G06T11/001 ,  G06T11/80 ,  G06F16/5838 ,  G06N3/0454 ,  G06F16/538

Abstract: A method and system for color optimization in generated images are described. The method and system include receiving an image generation prompt that includes a text description of target image content and color information describing a target color palette; encoding the image generation prompt to obtain image features that represent the target image content and the target color palette; and generating an image representing the target image content with the target color palette based on the image features.

公开(公告)号：US20230185844A1

公开(公告)日：2023-06-15

申请号：US18104848

申请日：2023-02-02

Applicant: Adobe Inc.

Inventor： Pranav Vineet Aggarwal ,  Zhe Lin ,  Baldo Antonio Faieta ,  Saeid Antonio Motiian

IPC: G06F16/583 ,  G06N20/00 ,  G06N3/08 ,  G06F16/538 ,  G06F18/21 ,  G06F18/22 ,  G06V30/19 ,  G06V30/262 ,  G06V10/82 ,  G06V10/94

CPC classification number: G06F16/583 ,  G06N20/00 ,  G06N3/08 ,  G06F16/538 ,  G06F18/21 ,  G06F18/22 ,  G06V30/19147 ,  G06V30/1916 ,  G06V30/19173 ,  G06V30/274 ,  G06V10/82 ,  G06V10/945 ,  G10L15/22

Abstract: Visually guided machine-learning language model and embedding techniques are described that overcome the challenges of conventional techniques in a variety of ways. In one example, a model is trained to support a visually guided machine-learning embedding space that supports visual intuition as to “what” is represented by text. The visually guided language embedding space supported by the model, once trained, may then be used to support visual intuition as part of a variety of functionality. In one such example, the visually guided language embedding space as implemented by the model may be leveraged as part of a multi-modal differential search to support search of digital images and other digital content with real-time focus adaptation which overcomes the challenges of conventional techniques.

公开(公告)号：US11500939B2

公开(公告)日：2022-11-15

申请号：US16854697

申请日：2020-04-21

Applicant: Adobe Inc.

Inventor： Pranav Vineet Aggarwal ,  Ali Aminian ,  Ajinkya Gorakhnath Kale ,  Aashish Kumar Misraa

IPC: G06F7/00 ,  G06F16/903 ,  G06N20/00 ,  G06F16/908 ,  G06K9/62

Abstract: Technology is disclosed herein for enhanced similarity search. In an implementation, a search environment includes one or more computing hardware, software, and/or firmware components in support of enhanced similarity search. The one or more components identify a modality for a similarity search with respect to a query object. The components generate an embedding for the query object based on the modality and based on connections between the query object and neighboring nodes in a graph. The embedding for the query object provides the basis for the search for similar objects.