-
公开(公告)号：US20240428586A1
公开(公告)日：2024-12-26
申请号：US18827088
申请日：2024-09-06
Applicant: Google LLC
Inventor： Anurag Arnab , Mostafa Dehghani , Georg Heigold , Chen Sun , Mario Lucic , Cordelia Luise Schmid
Abstract: A computer-implemented method for classifying video data with improved accuracy includes obtaining, by a computing system comprising one or more computing devices, video data comprising a plurality of video frames; extracting, by the computing system, a plurality of spatiotemporal representations from the video data, the plurality of spatiotemporal representations comprising a representation of spatiotemporal information in the video data; providing, by the computing system, the plurality of spatiotemporal representations as input to a video understanding model, the video understanding model comprising a video transformer encoder model; and receiving, by the computing system, a classification output from the video understanding model.
-
公开(公告)号：US20240346824A1
公开(公告)日：2024-10-17
申请号：US18634794
申请日：2024-04-12
Applicant: Google LLC
Inventor： Alexey Alexeevich Gritsenko , Xuehan Xiong , Josip Djolonga , Mostafa Dehghani , Chen Sun , Mario Lucic , Cordelia Luise Schmid , Anurag Arnab
IPC: G06V20/40 , G06T7/73 , G06V10/62 , G06V10/764 , G06V10/77 , G06V10/774 , G06V10/776 , G06V10/82
CPC classification number: G06V20/46 , G06T7/73 , G06V10/62 , G06V10/764 , G06V10/7715 , G06V10/774 , G06V10/776 , G06V10/82 , G06T2207/10016 , G06T2207/20081 , G06T2207/20084
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing action localization on an input video. In particular, a system maintains a set of query vectors and uses the input video and the set of query vectors to generate an action localization output for the input video. The action localization output includes, for each of one or more agents depicted in the video, data specifying, for each of one or more video frames in the video, a respective bounding box in the video frame that depicts the agent and a respective action from a set of actions that is being performed by the agent in the video frame.
-
公开(公告)号：US20180232344A1
公开(公告)日：2018-08-16
申请号：US15950335
申请日：2018-04-11
Applicant: Google LLC
CPC classification number: G06F17/2247 , G06F16/951 , G06F17/248
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining summary content for resources in a domain. In one aspect, a method includes accessing a first resource belonging to a particular domain, selecting an anchor in the first resource linking to a second resource belonging to the particular domain, identifying particular text content in the first resource that is subordinate to the anchor that the second resource includes the particular text content that is subordinate to the anchor, based on determining that the second resource includes the particular text content that is subordinate to the anchor, generating a domain template for the particular domain, the domain template specifying a location of the particular text content in the second resource, and determining, for each respective resource belonging to the particular domain having a structure matching the domain template, respective text content for the respective resource.
-
公开(公告)号：US11907337B2
公开(公告)日：2024-02-20
申请号：US17046313
申请日：2019-11-18
Applicant: Google LLC
Inventor： Ariel Fuxman , Aleksei Timofeev , Zhen Li , Chun-Ta Lu , Manan Shah , Chen Sun , Krishnamurthy Viswanathan , Chao Jia
IPC: G06K9/62 , G06K9/46 , G06F18/24 , G06F18/214 , G06F18/2413
CPC classification number: G06F18/24 , G06F18/214 , G06F18/24147
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for realizing a multimodal image classifier. In an aspect, a method includes, for each image of a plurality of images: processing the image by a textual generator model to obtain a set of phrases that are descriptive of the content of the image, wherein each phrase is one or more terms, processing the set of phrases by a textual embedding model to obtain an embedding of predicted text for the image, and processing the image using an image embedding model to obtain an embedding of image pixels of the image. Then a multimodal image classifier is trained on the embeddings of predicted text for the images and the embeddings of image pixels for the images to produce, as output, labels of an output taxonomy to classify an image based on the image as input.
-
公开(公告)号：US11163989B2
公开(公告)日：2021-11-02
申请号：US16637960
申请日：2019-08-06
Applicant: Google LLC
Inventor： Chen Sun , Abhinav Shrivastava , Cordelia Luise Schmid , Rahul Sukthankar , Kevin Patrick Murphy , Carl Martin Vondrick
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing action localization in images and videos. In one aspect, a system comprises a data processing apparatus; a memory in data communication with the data processing apparatus and storing instructions that cause the data processing apparatus to perform image processing and video processing operations comprising: receiving an input comprising an image depicting a person; identifying a plurality of context positions from the image; determining respective feature representations of each of the context positions; providing a feature representation of the person and the feature representations of each of the context positions to a context neural network to obtain relational features, wherein the relational features represent relationships between the person and the context positions; and determining an action performed by the person using the feature representation of the person and the relational features.
-
Patent Agency Ranking
公开(公告)号：US20250053753A1
公开(公告)日：2025-02-13
申请号：US18448508
申请日：2023-08-11
Applicant: Google LLC
Inventor： Xingyi Zhou , Anurag Arnab , Chen Sun , Cordelia Luise Schmid
IPC: G06F40/40 , G06T7/246 , G06V10/22 , G06V10/774 , G06V10/776 , G06V20/40
Abstract: Provided are a new task and model for dense video object captioning—detecting, tracking, and captioning trajectories of all objects in a video. This task unifies spatial and temporal understanding of the video, and requires fine-grained language description. Example implementations of the proposed model for dense video object captioning can be trained end-to-end and can include different models for spatial localization, tracking, and captioning. As such, some example implementations of the present disclosure can train the proposed model with a mixture of disjoint tasks, and leverage diverse, large-scale datasets which supervise different parts of an example proposed model. This results in noteworthy zero-shot performance.
-
公开(公告)号：US20240428587A1
公开(公告)日：2024-12-26
申请号：US18827133
申请日：2024-09-06
Applicant: Google LLC
Inventor： Anurag Arnab , Mostafa Dehghani , Georg Heigold , Chen Sun , Mario Lucic , Cordelia Luise Schmid
Abstract: A computer-implemented method for classifying video data with improved accuracy includes obtaining, by a computing system comprising one or more computing devices, video data comprising a plurality of video frames; extracting, by the computing system, a plurality of video tokens from the video data, the plurality of video tokens comprising a representation of spatiotemporal information in the video data; providing, by the computing system, the plurality of video tokens as input to a video understanding model, the video understanding model comprising a video transformer encoder model; and receiving, by the computing system, a classification output from the video understanding model.
-
公开(公告)号：US12112538B2
公开(公告)日：2024-10-08
申请号：US17370522
申请日：2021-07-08
Applicant: Google LLC
Inventor： Anurag Arnab , Mostafa Dehghani , Georg Heigold , Chen Sun , Mario Lucic , Cordelia Luise Schmid
Abstract: A computer-implemented method for classifying video data with improved accuracy includes obtaining, by a computing system comprising one or more computing devices, video data comprising a plurality of video frames; extracting, by the computing system, a plurality of video tokens from the video data, the plurality of video tokens comprising a representation of spatiotemporal information in the video data; providing, by the computing system, the plurality of video tokens as input to a video understanding model, the video understanding model comprising a video transformer encoder model; and receiving, by the computing system, a classification output from the video understanding model.
-
公开(公告)号：US20230229714A1
公开(公告)日：2023-07-20
申请号：US18150739
申请日：2023-01-05
Applicant: Google LLC
IPC: G06F16/951 , G06F40/143 , G06F40/186
CPC classification number: G06F16/951 , G06F40/143 , G06F40/186
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining summary content for resources in a domain. In one aspect, a method includes accessing a first resource belonging to a particular domain, selecting an anchor in the first resource linking to a second resource belonging to the particular domain, identifying particular text content in the first resource that is subordinate to the anchor that the second resource includes the particular text content that is subordinate to the anchor, based on determining that the second resource includes the particular text content that is subordinate to the anchor, generating a domain template for the particular domain, the domain template specifying a location of the particular text content in the second resource, and determining, for each respective resource belonging to the particular domain having a structure matching the domain template, respective text content for the respective resource.
-
公开(公告)号：US11580177B2
公开(公告)日：2023-02-14
申请号：US17065256
申请日：2020-10-07
Applicant: Google LLC
IPC: G06F16/951 , G06F40/186 , G06F40/143
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining summary content for resources in a domain. In one aspect, a method includes accessing a first resource belonging to a particular domain, selecting an anchor in the first resource linking to a second resource belonging to the particular domain, identifying particular text content in the first resource that is subordinate to the anchor that the second resource includes the particular text content that is subordinate to the anchor, based on determining that the second resource includes the particular text content that is subordinate to the anchor, generating a domain template for the particular domain, the domain template specifying a location of the particular text content in the second resource, and determining, for each respective resource belonging to the particular domain having a structure matching the domain template, respective text content for the respective resource.
-
-
-
-
-
-
-
-
-
Search Results
18
records
(took 0.014 seconds)
