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[KDD'2026] "VideoRAG: Chat with Your Videos"

Vimo: Chat with Your Videos

VideoRAG: Chat with Your Videos โ€ข Vimo Desktop

HKUDS%2FVideoRAG | Trendshift

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๐ŸŽฌ Intelligent Video Conversations | Powered by Advanced AI | Extreme Long-Context Processing


Vimo is a revolutionary desktop application that lets you chat with your videos using cutting-edge AI technology. Built on the powerful VideoRAG framework, Vimo can understand and analyze videos of any length - from short clips to hundreds of hours of content - and answer your questions with remarkable accuracy.

๐ŸŽฅ Watch Vimo in Action

See how Vimo transforms video interaction with intelligent conversations and deep understanding capabilities.

Vimo Introduction Video

๐Ÿ‘† Click to watch the Vimo demo video

โœจ Key Features

For Everyone

  • Drag & Drop Upload: Simply drag video files into Vimo
  • Smart Conversations: Ask questions in natural language
  • Multi-Format Support: Works with MP4, MKV, AVI, and more
  • Cross-Platform: Available on macOS, Windows, and Linux

For Power Users

  • Extreme Long Videos: Process videos up to hundreds of hours
  • Multi-Video Analysis: Compare and analyze multiple videos simultaneously
  • Advanced Retrieval: Find specific moments and scenes with precision
  • Export Capabilities: Save insights and references for later use

For Researchers

  • VideoRAG Framework: Access to cutting-edge retrieval-augmented generation
  • Benchmark Dataset: LongerVideos benchmark with 134+ hours of content
  • Performance Metrics: Detailed evaluation against existing methods
  • Extensible Architecture: Build upon our open-source foundation

๐ŸŒŸ Why Vimo?

For Video Enthusiasts & Professionals:

  • Effortless Video Analysis: Upload any video and start asking questions immediately
  • Natural Conversations: Chat with your videos as if talking to a human expert
  • No Length Limits: Process everything from 30-second clips to 100+ hour documentaries
  • Deep Understanding: Combines visual content, audio, and context for comprehensive answers

For Researchers & Developers:

  • State-of-the-Art Algorithm: Built on VideoRAG, featuring graph-driven knowledge indexing
  • Benchmark Performance: Evaluated on 134+ hours across lectures, documentaries, and entertainment
  • Open Source: Full access to VideoRAG implementation and research findings
  • Scalable Architecture: Efficient processing with single GPU (RTX 3090) capability

๐Ÿ“‹ Table of Contents

  • ๐Ÿš€ Quick Start
  • โœจ Key Features
  • ๐Ÿ”ฌ VideoRAG Algorithm
  • ๐Ÿ› ๏ธ Development Setup
  • ๐Ÿงช Benchmarks & Evaluation
  • ๐Ÿ“– Citation
  • ๐Ÿค Contributing
  • ๐Ÿ™ Acknowledgement

๐Ÿš€ Quick Start of Vimo

Option 1: Download Vimo App (Coming Soon)

[!NOTE] We are preparing the Beta release for macOS Apple Silicon first, with Windows and Linux versions coming soon!

Option 2: Run from Source Code

For detailed setup instructions:

  • Vimo Desktop App: See Vimo-desktop for complete installation and configuration steps

Quick Overview:

  1. Set up the Python backend environment and start the VideoRAG server
  2. Launch the Electron frontend application
  3. Start chatting with your videos!

๐Ÿ”ฌ VideoRAG Algorithm

VideoRAG Architecture

VideoRAG introduces a novel dual-channel architecture that combines:

  • Graph-Driven Knowledge Indexing: Multi-modal knowledge graphs for structured video understanding
  • Hierarchical Context Encoding: Preserves spatiotemporal visual patterns across long sequences
  • Adaptive Retrieval: Dynamic retrieval mechanisms optimized for video content
  • Cross-Video Understanding: Semantic relationship modeling across multiple videos

Technical Highlights

  • Efficient Processing: Handle hundreds of hours on a single RTX 3090 (24GB)
  • Structured Indexing: Distill long videos into concise knowledge representations
  • Multi-Modal Retrieval: Align textual queries with visual and audio content
  • LongerVideos Benchmark: 160+ videos, 134+ hours across diverse domains

Performance Comparison

Our VideoRAG algorithm significantly outperforms existing methods in long-context video understanding:

Performance Comparison

Experiments and Evaluation

See VideoRAG-algorithm for detailed development setup including:

  • Conda environment creation
  • Model checkpoints download
  • Dependencies installation
  • Evaluation scripts

๐Ÿงช LongerVideos Benchmark

We created the LongerVideos benchmark to evaluate long-context video understanding:

Video Type #Collections #Videos #Queries Avg. Duration
Lectures 12 135 376 ~64.3 hours
Documentaries 5 12 114 ~28.5 hours
Entertainment 5 17 112 ~41.9 hours
Total 22 164 602 ~134.6 hours

For detailed evaluation instructions and reproduction scripts, see VideoRAG-algorithm/reproduce.

๐Ÿ“– Citation

If you find Vimo or VideoRAG helpful in your research, please cite our paper:

@article{VideoRAG,
  title={VideoRAG: Retrieval-Augmented Generation with Extreme Long-Context Videos},
  author={Ren, Xubin and Xu, Lingrui and Xia, Long and Wang, Shuaiqiang and Yin, Dawei and Huang, Chao},
  journal={arXiv preprint arXiv:2502.01549},
  year={2025}
}

๐Ÿค Contributing

We welcome contributions from the community! Whether you're:

  • Reporting bugs or suggesting features for Vimo
  • Improving VideoRAG algorithms or adding new capabilities
  • Enhancing documentation or creating tutorials
  • Designing UI/UX improvements for better user experience

Feel free to submit issues and pull requests. Together, we're building the future of intelligent video interaction!

๐Ÿ™ Acknowledgement

Vimo builds upon the incredible work of the open-source community:

๐ŸŒŸ Transform how you interact with videos. Start your journey with Vimo today!


Built with โค๏ธ by the VideoRAG@HKUDS team.