Swin Transformer - Paper Explained

[@VedantJoshi-mr2us]

By far one of the best + complete, SWIN transformer explanations on the entire Internet.

[@soroushmehraban]

Thanks!

[@FinalProject-rw1yf]

@@soroushmehraban Hi sir, could you also explain the FasterViT and GCViT paper...

[@omarabubakr6408]

That's The Most Illustrative Video Of Swin-Transformers on The Internet!

[@soroushmehraban]

Glad you enjoyed it 😃

[@omarabubakr6408]

@@soroushmehraban yes abs thx so much, although I Have a Quick Question More Related to PyTorch actually which is in min 12:49 in line 239 in the code 1st what does -1 here means and what does it do exactly with the tensor 2nd from where we get [4,16] the 4 here from where we got it cuz its not mentioned in the reshaping. Thanks in advance.

[@SizzleSan]

Thorough! Very comprehensible, thank you.

[@yehanwasura]

Really informative, helped me lot to understand many concepts here. Keep up the good work

[@soroushmehraban]

Thanks! I’ll try my best.

[@kundankumarmandal6804]

You deserve more likes and subscribers

[@soroushmehraban]

Thanks man🙂 appreciated

[@rohollahhosseyni8564]

Very well explained, thank you Soroush.

[@soroushmehraban]

Glad you liked it

[@antonioperezvelasco3297]

Thanks for the good explanation!

[@SaniaEskandari]

perfect description.

[@soroushmehraban]

Glad it was helpful 🙂

[@proteus333]

Amazing video !

[@soroushmehraban]

Thanks!

[@akbarmehraban5007]

I enjoy very much

[@dslkgjsdlkfjd]

2:43 C would be equal to the number of filters not the number of kernels. In the torch.nn.conv2d operation being performed we have 3 kernels for each input channel and then C number of filters. Each filter having 3 kernels not C number of kernels.

[@siarez]

Great video! Thanks

[@soroushmehraban]

Thanks for the feedback 🙂

[@pradyumagarwal3978]

where is the code that u were referring to?

[@soroushmehraban]

github.com/microsoft/Swin-Transformer/blob/main/models/swin_transformer.py#L222

[@Karthik-kt24]

very nicely explained thank you! likes are at 314 so didnt hit like it😁subbed instead