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Hi, I saw on a paper that he used the res2net_v1b code you posted, and I m not sure if this paper was published by you, so I wanted to ask if I can use the res2net_v1b code you posted for my paper experiments? ...
  • Summerx026
  • 2
  • Opened 
    on Jan 30, 2024
  • #77

代码: spx = torch.split(out, self.width, 1) for i in range(self.nums): if i==0 or self.stype== stage : sp = spx[i] else: sp = sp + spx[i] sp = self.convsi sp = self.relu(self.bnsi) if i==0: out = sp else: ...
  • VagoLapis
  • 1
  • Opened 
    on Jan 11, 2024
  • #76

Is it possible to provide the self-supervised pre-trained model? Specifically, the model is trained on Imagenet without using the ground truth label. The model is trained in an self-supervised manner, ...
  • ForawardStar
  • Opened 
    on Oct 11, 2023
  • #75

Hi, Dr. Gao, I have a question about model modification. Due to my work setting, I could only set batch_size=1, so I am going to modify the BatchNorm to GroupNorm. Based on the original code, I just changed ...
  • CinKKKyo
  • Opened 
    on Jun 7, 2023
  • #74

Hi, I am the author of SSLD. I noticed that the weight of SSLD has been added to your repo, but here it should be Res2Net-D instead of ResNet-B. I hope you can confirm it at your convenience.
  • cuicheng01
  • 3
  • Opened 
    on Dec 8, 2022
  • #72

您好,我现在在复现res2net在imagenet数据集上的分类精度,我参考了论文,res2net50的训练策略如下: scheduler: step_decay lr: 0.1 warmup_epochs: 0 decay_rate: 0.1 decay_epochs: 30 epoch_size: 100 res2net精度可以达到top1: 78.00%,和论文是相符的; 在此基础上添加了cutmix数据增强策略,epoch_size变为300,每75epoch学习率下降为原来的0.1,来训练res2net50-v1b;res2net50-v1b实测精度只有79.80%,与论文相比还差0.5%。因为代码中没有提供训练的参数,可能在某些地方没对齐,想问一下能不能分享一下res2net50-v1b的训练策略或者训练参数。谢谢。 ...
  • zp5070
  • 2
  • Opened 
    on Nov 2, 2022
  • #71

看res2net的layer1部分:26*4 = 104 ==conv1x1== 256 想减小通道数,把256 改成 64 请问,可以把26改成13,或者更小吗?会有什么不好的影响吗 比如下面: ① 134 = 52 ==conv1x1== 64 ② 74 = 28 ==conv1x1== 64 谢谢
  • laocan
  • 2
  • Opened 
    on Sep 23, 2022
  • #70

你好请问 for i in range(self.nums): if i==0 or self.stype== stage : sp = spx[i] else: sp = sp + spx[i] //这里因为两个特征的尺寸不一样并不能加在一起啊?一个是64一个是128
  • kirkzZ
  • 1
  • Opened 
    on Aug 8, 2022
  • #68
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