mlsanityData to 14 Oct 2026

A Similarity Alignment Model for Video Copy Segment Matching

arXiv 2305.15679 ↗First posted 25 May 2023cs.CVcited by 3

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Abstract (arXiv)

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 report, we share our winner solutions on Matching Track. We propose a Similarity Alignment Model(SAM) for video copy segment matching. Our SAM exhibits superior performance compared to other competitors, with a 0.108 / 0.144 absolute improvement over the second-place competitor in Phase 1 / Phase 2. Code is available at https://github.com/FeipengMa6/VSC22-Submission/tree/main/VSC22-Matching-Track-1st.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 3 of its 7 references that are in the map. First posted on arXiv 25 May 2023.

Builds on

3 of 7 references.

References · 3

  1. 2019Searching for MobileNetV3cited by 1,994
  2. 2019Deep High-Resolution Representation Learning for Human Pose Estimationcited by 1,339
  3. 2022TransVCL: Attention-enhanced Video Copy Localization Network with Flexible Supervisioncited by 15

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 1; 2025: 0; 2026: 1.

3 papers.