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The Video Browser Showdown (VBS) challenges systems to deliver accurate results under strict time constraints. To meet this demand, we present Fusionista2.0, a streamlined video retrieval system optimized for speed and usability. All core modules were re-engineered for efficiency: preprocessing now relies on ffmpeg for fast keyframe extraction, Optical Character Recognition (OCR) is powered by Vintern-1B-v3.5 for robust multilingual text recognition, and Automatic Speech Recognition (ASR) employs faster-whisper for real-time transcription. For question answering, lightweight vision–language models provide quick responses without the heavy cost of large models. Beyond these technical upgrades, Fusionista2.0 introduces a redesigned UI/UX with improved responsiveness, accessibility, and workflow efficiency, enabling even non-expert users to retrieve relevant content rapidly. Evaluations demonstrate that retrieval time was reduced by up to 75% while accuracy and user satisfaction both increased, confirming Fusionista2.0 as a competitive and user-friendly system for large-scale video search.

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Fusionista2.0: Efficiency Retrieval System for Large-Scale Datasets

  • 会议论文

  • 发表日期：

    2026年

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  • Huy M. Le,
  • Dat Tien Nguyen,
  • Phuc Binh Nguyen,
  • Gia Bao Le Tran,
  • Phu Truong Thien,
  • Cuong Dinh,
  • Minh Nguyen,
  • Nga Nguyen,
  • Thuy T. N. Nguyen,
  • Huy Gia Ngo,
  • Tan Nhat Nguyen,
  • Binh T. Nguyen

摘要

The Video Browser Showdown (VBS) challenges systems to deliver accurate results under strict time constraints. To meet this demand, we present Fusionista2.0, a streamlined video retrieval system optimized for speed and usability. All core modules were re-engineered for efficiency: preprocessing now relies on ffmpeg for fast keyframe extraction, Optical Character Recognition (OCR) is powered by Vintern-1B-v3.5 for robust multilingual text recognition, and Automatic Speech Recognition (ASR) employs faster-whisper for real-time transcription. For question answering, lightweight vision–language models provide quick responses without the heavy cost of large models. Beyond these technical upgrades, Fusionista2.0 introduces a redesigned UI/UX with improved responsiveness, accessibility, and workflow efficiency, enabling even non-expert users to retrieve relevant content rapidly. Evaluations demonstrate that retrieval time was reduced by up to 75% while accuracy and user satisfaction both increased, confirming Fusionista2.0 as a competitive and user-friendly system for large-scale video search.