English

A Dual-level Detection Method for Video Copy Detection

Computer Vision and Pattern Recognition 2023-05-23 v1

Abstract

With the development of multimedia technology, Video Copy Detection has been a crucial problem for social media platforms. Meta AI hold Video Similarity Challenge on CVPR 2023 to push the technology forward. In this paper, we share our winner solutions on both tracks to help progress in this area. For Descriptor Track, we propose a dual-level detection method with Video Editing Detection (VED) and Frame Scenes Detection (FSD) to tackle the core challenges on Video Copy Detection. Experimental results demonstrate the effectiveness and efficiency of our proposed method. Code is available at https://github.com/FeipengMa6/VSC22-Submission.

Keywords

Cite

@article{arxiv.2305.12361,
  title  = {A Dual-level Detection Method for Video Copy Detection},
  author = {Tianyi Wang and Feipeng Ma and Zhenhua Liu and Fengyun Rao},
  journal= {arXiv preprint arXiv:2305.12361},
  year   = {2023}
}
R2 v1 2026-06-28T10:40:21.788Z