Comments (3)
There are also questions about the design of layer_scale.
VAN-Classification/models/van.py
Line 96 in d94f156
from van-classification.
We adopte the same strategy with this paper.
In practice, we found we can achieve better results with dynamic weights, but it introduced some additional computational and memory overhead
from van-classification.
We adopte the same strategy with this paper.
In practice, we found we can achieve better results with dynamic weights, but it introduced some additional computational and memory overhead
thx
from van-classification.
Related Issues (20)
- [Question] Object detection and instance segmentation HOT 2
- Question related to permutation operation used in the model HOT 1
- configuration for pre-trained models HOT 1
- Issue about training HOT 3
- The model used for classification problem HOT 2
- OverlapPatchEmbed HOT 6
- Why not use SyncBN HOT 2
- Code for detection HOT 1
- Why use .clone() for shortcut connection? HOT 1
- code for visualization
- RuntimeError: cuDNN error: CUDNN_STATUS_NOT_INITIALIZED HOT 1
- 22k finetune 1k pretrained weights
- where is the detection model?
- Class activation mapping (CAM) Target Layer HOT 1
- how to understand large kernel convolution decomposition?
- Attention vs Add in LKA HOT 1
- question on the number of parameter HOT 1
- Decomposition diagram of large-kernel convolution
- Attention模块代码中的shortcut
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