Visual Relationship Detection with AI

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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