Added video processing section (Unit 7 - Transformers based models)

[mreraser]

Co-authored-by: seoulsky-field
seoulsky.field02@gmail.com

What does this PR do?

Added Transformers based models at video processing section. This document provides an overview of how Transformer models are applied in video processing, focusing on the Vision Transformer (ViT) and its video-specific variant, the Video Vision Transformer (ViViT), and TimeSFormer model.

Thank you in advance for your review.

Part of Proposed Outline Revision for Unit 7. Video & Video Processing / dicussions #348

Who can review?

@jungnerd @cjfghk5697 @1kmmk1 and anyone who wants to review!

Who can review (Final)

[jungnerd]

Fixed minor typos and suggested the name of the anchor.
Other than that, everything looks good to me 👍🏻

[johko]

Thanks for the contribution @mreraser !
I think the main base for most my comments is that we need to keep in mind that the course should also be good to read for beginners. I think sometimes you assume a bit too much prior knowledge, adding some more background info here and there would already be really great.

But apart from that it is a great piece of education, I already learned quite a few things just from reading through it once. Thank you so much for the effort 🤗

[johko]

I'm not exactly sure how these blocks will look in HF markdown (once again), as currently the preview is missing because of the persisting token error. So I will just assume it is alright for now, but once we can see how it really looks in the docs, you might need to change it.

[mreraser]

Yes I understand, and I’ll make adjustments if any issues arise in the future.

[johko]

Could you add some words here about what embeddings are and why it is important (just a short info for beginners). And also say why you will explain Uniform Frame Sampling and Tubelet Embeddings. Right now I feel like this part is missing some context.

[mreraser]

@johko Thank you very much for your review! 😄 I will carefully read through the details you provided and make the necessary revisions accordingly.

[mreraser]

Hello @johko! 😃

I have carefully reviewed your feedback and addressed the points you mentioned as follows:

1. Removed all anchor points
2. Fixed minor typos
3. Added an explanation of embeddings and their importance
4. Clarified the reason for discussing Uniform Frame Sampling and Tubelet Embeddings
5. Provided a definition of spatio-temporal tokens
6. Explained the term "contextualize"
7. Defined n_w, n_h, and n_t earlier in the text

Thank you for your guidance, and please let me know if there’s anything else you’d like me to improve!

[johko]

Thank you for the changes 🙂
LGTM 👍

[mreraser]

Thank you for the changes 🙂 LGTM 👍

Thank you @johko 👍 I also resolved some toctree conflits. Have a good one!

[ATaylorAerospace]

Great additions..LGTM!