Generating Adjacency Matrix for Video Relocalization
Computer Vision and Pattern Recognition
2022-01-28 v2 Machine Learning
Image and Video Processing
Abstract
In this paper, we continue our work on video relocalization task. Based on using graph convolution to extract intra-video and inter-video frame features, we improve the method by using similarity-metric based graph convolution, whose weighted adjacency matrix is achieved by calculating similarity metric between features of any two different time steps in the graph. Experiments on ActivityNet v1.2 and Thumos14 dataset show the effectiveness of this improvement, and it outperforms the state-of-the-art methods.
Keywords
Cite
@article{arxiv.2008.08977,
title = {Generating Adjacency Matrix for Video Relocalization},
author = {Yuan Zhou and Mingfei Wang and Ruolin Wang and Shuwei Huo},
journal= {arXiv preprint arXiv:2008.08977},
year = {2022}
}
Comments
arXiv admin note: substantial text overlap with arXiv:2007.09877