Comments (2)
Thank you for your interest.
RPB is relative positional biases, they're learnable biases that are added to attention weights.
They're widely used especially in restricted attention patterns, such as Swin's WSA, and we adopted that into NA.
You can refer to these works for more information.
https://arxiv.org/abs/1711.11575
https://arxiv.org/abs/1904.11491
https://arxiv.org/abs/1910.10683
https://arxiv.org/abs/2002.12804
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@alihassanijr thanks for your timely response.
Thanks for your awesome work!
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Related Issues (20)
- Can you release your training log of NAT? I mean, the summary.csv in output folder. HOT 3
- ONNX HOT 2
- How to visualize the attention map? HOT 3
- Welcome update to OpenMMLab 2.0 HOT 1
- Is it possible to do upsampling using NAT ? HOT 2
- Where is natten.py
- May I ask whether the code of coco instance segmentation mask2former is dinat or NAT? HOT 1
- some problem during train HOT 9
- Is DiNAT code is runnable? HOT 2
- Is dectect model available? HOT 2
- freeze_at be set to 2 to freeze the pretrained weight downloaded from the official website? HOT 2
- About the receptive field of image pixel HOT 4
- NAT Tiny performance on ImageNet 1k HOT 7
- training from scratch with different size for height and width HOT 3
- Cannot repeat the results of Mask2Former+DiNAT-Large on ADE20K HOT 12
- mmdetection on COCO2017 not converge HOT 1
- How to calculate the number of params? HOT 1
- For 3D segmentation HOT 2
- instance segmentation mask2former + dinat HOT 1
- Some comparisons against Deformable Attention HOT 4
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