The goal of the Kinetics dataset is to help the computer vision and machine learning communities advance models for video understanding. Given this large human action classification dataset, it may be possible to learn powerful video representations that transfer to different video tasks.
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Resize your browser window so you can see both the website and your desktop simultaneously.
Only the Facebook icon. And it was huge.
But she never deleted it, either.
And the portal would open.
If you're looking for a specific look, here are various official and stylized Facebook icons you can use for your shortcut: File:Facebook Logo 2023.png - Wikimedia Commons Wikimedia Commons - Wikimedia.org
Click and hold the lock icon (or the small icon to the left of the URL) in the address bar.
This is the fastest way to get a Facebook icon on your desktop across any major browser like Chrome, Firefox, or Edge. Open your web browser and go to facebook.com.
This involves right-clicking the desktop -> New -> Shortcut -> typing in the URL https://www.facebook.com .
1. Possible to use ImageNet checkpoints?
We allow finetuning from public ImageNet checkpoints for the supervised track -- but a link to the specific checkpoint should be provided with each submission.
2. Possible to use optical flow?
Flow can be used as long as not trained on external datasets, except if they are synthetic.
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3. Can we train on test data without labels (e.g. transductive)?
No.
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4. Can we use semantic class label information?
Yes, for the supervised track.
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5. Will there be special tracks for methods using fewer FLOPs / small models or just RGB vs RGB+Audio in the self-supervised track?
We will ask participants to provide the total number of model parameters and the modalities used and plan to create special mentions for those doing well in each setting, but not specific tracks.