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  3. ClipScout
Thanh Nguyễn Vănabout 11 hours agoContributorJudging locked: Event build

ClipScout

An AI editorial assistant for video editors and content teams: turn a story brief into reviewed footage, identify missing shots, and export a first cut with a traceable source shot list.

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Project description
ClipScout helps video editors and content teams turn a story brief into a reviewed first cut. Instead of repeatedly watching archive footage, users define the shots they need, search the supplied video archive, and preview the original clips. VAST Data's VSS stack provides retrieval, using NVIDIA Cosmos Reason descriptions and Cosmos Embed matching. Our own Weights & Biases serverless inference call recommends candidate clips, a sequence, and potential coverage gaps from those descriptions. Editors verify the footage and approve each selection; AI suggestions never automatically change the cut. The demo assembles a cyclist, pedestrians crossing, and a wide highway view into a 15-second MP4. An unsupported marathon-finish request stays visibly unfilled. Users can reorder or remove shots and download both a silent MP4 and a JSON source shot list containing source IDs, original timecodes, and cut positions. A SpaceXAI/Cursor agent contributed the editorial advisor; Codex integrated, tested, and deployed the application. FFmpeg assembles the output. We verified a real W&B call, browser downloads, and 29 passing tests. This prototype works on recorded archive footage; live monitoring and crew dispatch are future work.
Tools used
  • VAST Data logoVAST Data
  • SpaceXAI (Cursor) logoSpaceXAI (Cursor)
  • CoreWeave (Weights & Biases) logoCoreWeave (Weights & Biases)
  • NVIDIA logoNVIDIA
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Project links
  • GitHub repository
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  • Demo video
Tools used
  • VAST Data logoVAST Data
  • SpaceXAI (Cursor) logoSpaceXAI (Cursor)
  • CoreWeave (Weights & Biases) logoCoreWeave (Weights & Biases)
  • NVIDIA logoNVIDIA