A Dual-level Detection Method for Video Copy Detection
Tianyi Wang Feipeng Ma Zhenhua Liu Fengyun Rao
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.