2019/03/26 by Noel Mizzi, Mizzi, Noel, Adrian Muscat +1
Computer Science · #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Human Pose and Action Recognition #Video Surveillance and Tracking Methods
paper · pdf · doi:10.48550/arxiv.1903.11029
openalex publication_date 2019/03/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Visual Relationship Detection is defined as, given an image composed of a subject and an object, the correct relation is predicted. To improve the visual part of this difficult problem, ten preprocessing methods were tested to determine whether the widely used Union method yields the optimal results. Therefore, focusing solely on predicate prediction, no object detection and linguistic knowledge were used to prevent them from affecting the comparison results. Once fine-tuned, the Visual Geometry Group models were evaluated using Recall@1, per-predicate recall, activation maximisations, class activation maps, and error analysis. From this research it was found that using preprocessing methods such as the Union-Without-Background-and-with-Binary-mask (Union-WB-and-B) method yields significantly better results than the widely used Union method since, as designed, it enables the Convolutional Neural Network to also identify the subject and object in the convolutional layers instead of solely in the fully-connected layers.