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Building the howto100m Video Corpus
Manage episode 240115961 series 1361404
Content provided by Kyle Polich. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Kyle Polich or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Video annotation is an expensive and time-consuming process. As a consequence, the available video datasets are useful but small. The availability of machine transcribed explainer videos offers a unique opportunity to rapidly develop a useful, if dirty, corpus of videos that are "self annotating", as hosts explain the actions they are taking on the screen.
This episode is a discussion of the HowTo100m dataset - a project which has assembled a video corpus of 136M video clips with captions covering 23k activities.
Related LinksThe paper will be presented at ICCV 2019
525 episodes
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Manage episode 240115961 series 1361404
Content provided by Kyle Polich. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Kyle Polich or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Video annotation is an expensive and time-consuming process. As a consequence, the available video datasets are useful but small. The availability of machine transcribed explainer videos offers a unique opportunity to rapidly develop a useful, if dirty, corpus of videos that are "self annotating", as hosts explain the actions they are taking on the screen.
This episode is a discussion of the HowTo100m dataset - a project which has assembled a video corpus of 136M video clips with captions covering 23k activities.
Related LinksThe paper will be presented at ICCV 2019
525 episodes
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