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US Patent 10592767 Interpretable counting in visual question answering

Patent 10592767 was granted and assigned to Salesforce.com, Inc. on March, 2020 by the United States Patent and Trademark Office.

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Patent abstractTimelineTable: Further ResourcesReferences
Is a
Patent
Patent
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Patent attributes

Patent Applicant
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Current Assignee
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
105927671
Patent Inventor Names
Caiming Xiong1
Richard Socher1
Alexander Richard Trott1
Date of Patent
March 17, 2020
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Patent Application Number
158822201
Date Filed
January 29, 2018
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Patent Citations
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US Patent 10346721 Training a neural network using augmented training datasets
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US Patent 10282663 Three-dimensional (3D) convolution with 3D batch normalization
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US Patent 10198671 Dense captioning with joint interference and visual context
Patent Citations Received
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US Patent 12086539 System and method for natural language processing using neural network with cross-task training
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US Patent 11487999 Spatial-temporal reasoning through pretrained language models for video-grounded dialogues
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US Patent 11416688 Learning dialogue state tracking with limited labeled data
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US Patent 11922303 Systems and methods for distilled BERT-based training model for text classification
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US Patent 11934781 Systems and methods for controllable text summarization
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US Patent 11934952 Systems and methods for natural language processing using joint energy-based models
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US Patent 11948665 Systems and methods for language modeling of protein engineering
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US Patent 11481636 Systems and methods for out-of-distribution classification
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Patent Primary Examiner
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Hadi Akhavannik
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Patent abstract

Approaches for interpretable counting for visual question answering include a digital image processor, a language processor, and a counter. The digital image processor identifies objects in an image, maps the identified objects into an embedding space, generates bounding boxes for each of the identified objects, and outputs the embedded objects paired with their bounding boxes. The language processor embeds a question into the embedding space. The scorer determines scores for the identified objects. Each respective score determines how well a corresponding one of the identified objects is responsive to the question. The counter determines a count of the objects in the digital image that are responsive to the question based on the scores. The count and a corresponding bounding box for each object included in the count are output. In some embodiments, the counter determines the count interactively based on interactions between counted and uncounted objects.

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