mlsanityData to 7 Oct 2026

Marine Video Kit: A New Marine Video Dataset for Content-based Analysis and Retrieval

arXiv 2209.11518 ↗First posted 23 Sep 2022cs.CV cs.IR cs.MMcited by 9

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Abstract (arXiv)

Effective analysis of unusual domain specific video collections represents an important practical problem, where state-of-the-art general purpose models still face limitations. Hence, it is desirable to design benchmark datasets that challenge novel powerful models for specific domains with additional constraints. It is important to remember that domain specific data may be noisier (e.g., endoscopic or underwater videos) and often require more experienced users for effective search. In this paper, we focus on single-shot videos taken from moving cameras in underwater environments, which constitute a nontrivial challenge for research purposes. The first shard of a new Marine Video Kit dataset is presented to serve for video retrieval and other computer vision challenges. Our dataset is used in a special session during Video Browser Showdown 2023. In addition to basic meta-data statistics, we present several insights based on low-level features as well as semantic annotations of selected keyframes. The analysis also contains experiments showing limitations of respected general purpose models for retrieval. Our dataset and code are publicly available at https://hkust-vgd.github.io/marinevideokit.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 8 of its 24 references that are in the map. First posted on arXiv 23 Sep 2022.

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8 of 24 references.

References · 8

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2021Prefix-Tuning: Optimizing Continuous Prompts for Generationcited by 3,878
  3. 2017Dense-Captioning Events in Videoscited by 789
  4. 2017Towards Automatic Learning of Procedures from Web Instructional Videoscited by 616
  5. 2021ClipCap: CLIP Prefix for Image Captioningcited by 557
  6. 2018A Joint Sequence Fusion Model for Video Question Answering and Retrievalcited by 208
  7. 2018Enhancing Underwater Imagery using Generative Adversarial Networkscited by 94
  8. 2018V3C - a Research Video Collectioncited by 12

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Citing papers per year: 2023: 1; 2024: 3; 2025: 5.

9 papers.