Visual Relationship Detection with AI: Unterschied zwischen den Versionen
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= Abstract = | |||
Visual Relationship Detection (VRD) enables machines to go beyond object detection and recognize how objects interact within an image. This project combines a pre-trained YOLOv2 deep learning model in MATLAB with heuristic rules to detect object-object relationships, such as “person riding a bicycle” or “dog under table.” Additionally, we evaluate multiple VRD 2 approaches using a Zwicky Box based on technical criteria like accuracy, interpretability, and computational cost. The project is fully documented in a wiki, supported by visualizations. | |||
=Task= | =Task= | ||
Visual Relationship Detection: This involves identifying the relationships between objects within an image, such as “person riding a bicycle” or “dog under a table”. This task requires not just recognizing the objects but understanding their interactions. | Visual Relationship Detection: This involves identifying the relationships between objects within an image, such as “person riding a bicycle” or “dog under a table”. This task requires not just recognizing the objects but understanding their interactions. | ||
Version vom 11. April 2025, 23:22 Uhr
Abstract
Visual Relationship Detection (VRD) enables machines to go beyond object detection and recognize how objects interact within an image. This project combines a pre-trained YOLOv2 deep learning model in MATLAB with heuristic rules to detect object-object relationships, such as “person riding a bicycle” or “dog under table.” Additionally, we evaluate multiple VRD 2 approaches using a Zwicky Box based on technical criteria like accuracy, interpretability, and computational cost. The project is fully documented in a wiki, supported by visualizations.
Task
Visual Relationship Detection: This involves identifying the relationships between objects within an image, such as “person riding a bicycle” or “dog under a table”. This task requires not just recognizing the objects but understanding their interactions.
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