Comments (1)
- bottleneck里3个BN层,加在前两个位置结果差不多,在第三个位置可能会破坏与identity path的alignment.
- 关于比较复杂的组合的详细讨论不是本文的重点,本文主要是提供了IBN-a/b这两种较为简洁的方案,基于两个规则:1)适量引入IN保留大部分BN, 2)不在网络深层使用IN
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Related Issues (20)
- How to use res50 model retrain res50-ibna? HOT 1
- does IBN-Net suitable for VGG networks?
- KeyError: 'module name can\'t contain "."' HOT 1
- Segmentation implementation HOT 3
- Feature Divergence Analysis
- senet50 pretrained model? HOT 1
- can't archive weights from the tar file HOT 3
- any plans for the resnet152 Ibn pretrained models?
- Hello, I used your resnet50 with ibna added, and the performance on the mixed data set is significantly reduced. What is the reason for this? The data set is multiple person reID data sets HOT 2
- can you provide se_resnet50_ibn_a pre_model HOT 1
- IncompatibleKeys(missing_keys=[], unexpected_keys=[])
- Do you have the pytorch 1.0 version's pretrained model? HOT 3
- can you provide resnet50_ibn_a pre_model? HOT 3
- Request more variants such as ResNet-18 HOT 2
- Crop size for Semantic Segmentation with IBN-Net
- ibn-b
- seresnext ibn occur memory leak
- Pre-trained model of resnet101_ibn_b
- 您好,您发布的预训练模型权重文件是在ImageNet上训练了几个epochs呢? HOT 1
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