Google llc (20240289981). Localization of Objects Encoded in Image Data in Accordance with Natural Language Queries simplified abstract
Contents
Localization of Objects Encoded in Image Data in Accordance with Natural Language Queries
Organization Name
Inventor(s)
Wei-Cheng Kuo of Santa Clara CA (US)
Fred Bertsch of Belmont CA (US)
Anthony J. Piergiovanni of Denver CO (US)
Mohammad Taghi Saffar of Santa Clara CA (US)
Anelia Angelova of Palo Alto CA (US)
Localization of Objects Encoded in Image Data in Accordance with Natural Language Queries - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240289981 titled 'Localization of Objects Encoded in Image Data in Accordance with Natural Language Queries
Simplified Explanation: The patent application describes a unified generalized visual localization architecture that can comprehend natural language queries, locate objects, and detect objects in images.
Key Features and Innovation:
- Enhanced performance on referring expression comprehension, object localization, and object detection tasks
- Utilization of machine-learned natural language and image models
- Ability to understand and answer natural localization questions, output multiple boxes, provide null results when objects are not present, and solve general detection tasks
Potential Applications: This technology can be applied in various fields such as image recognition, augmented reality, autonomous vehicles, and surveillance systems.
Problems Solved: The technology addresses the challenges of accurately localizing and detecting objects in images based on natural language queries.
Benefits:
- Improved accuracy and efficiency in object localization and detection tasks
- Enhanced user experience in interacting with visual content
- Potential for automation and optimization of various processes that rely on image analysis
Commercial Applications: The technology can be utilized in industries such as e-commerce, security, healthcare, and entertainment for tasks like product recognition, security monitoring, medical imaging analysis, and content creation.
Questions about Generalized Object Location: 1. How does the unified generalized visual localization architecture improve object detection tasks? 2. What are the potential real-world applications of this technology in different industries?
Frequently Updated Research: Researchers are constantly exploring new ways to enhance the performance and capabilities of machine learning models for object localization and detection in images. Stay updated on the latest advancements in this field for potential improvements in accuracy and efficiency.
Original Abstract Submitted
generally, the disclosure is directed to generalized objected location, where the located object is in accordance to a natural language (nl) query. more specifically, the embodiments include a unified generalized visual localization architecture. the architecture achieves enhanced performance on the following three tasks: referring expression comprehension, object localization, and object detection. the embodiments employ machine-learned nl models and/or image models. the architecture is enabled to understand and answer natural localization questions towards an image, to output multiple boxes, provide no output if the object is not present (e.g., a null result), as well as, solve general detection tasks.
