Comments (9)
Training res2net152 takes a lot of time. So you gonna have to wait for several weeks for res2net152_v1b. We will notify you once res2net152_v1b is released.
We find that the current res2net101_v1b achieves much better results compared with some large models such as resnet152, resnext152, and hrnet48w on many tasks such as classification and instance segmentation, object detection with much less computational cost (about half). Maybe you can try res2net101_v1b for now.
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We have trained the res2net152, and we are benchmarking it on downstream tasks. If everything goes right, you can expect the res2net152 within a week. Thanks for your interest and patience.
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Will a res2next v1b model be made available?
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I ask because the v1b models seem like an even bigger contribution than the original res2net proposal, so I'm especially interested in v1b weights.
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Are you intending to write a paper for Res2Net v1b? I'm finding it substantially much more robust to distribution shift than Res2Net and ResNet.
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The res2net_v1b_152 is now available on https://mailnankaieducn-my.sharepoint.com/:u:/g/personal/shgao_mail_nankai_edu_cn/ERLs1nrRZepNumQ0GQEYEpwBRnqByInWTjvZLzhlc2blSw?e=cbr0cZ
Due to the overfiting of too deep model, the top.1 error of res2net152_v1b is similar to the res2net101_v1b. We are still working on avoiding the overfiting. We will release a new version once we solve the overfiting problem.
Still, res2net_v1b_152 achieves better performance on downstream tasks such as object detection.
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Are you intending to write a paper for Res2Net v1b? I'm finding it substantially much more robust to distribution shift than Res2Net and ResNet.
Thanks for your feedback!
Res2Netv1b have some slight improvements compared with res2net. We are still working on the improvement of this version. Once everything is done, we will release a report or a paper.
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Still, res2net_v1b_152 achieves better performance on downstream tasks such as object detection.
Yes, it also had better downstream performance than Res2Netv1b 101 on my robustness tasks.
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If you have code for a Res2NeXt v1b and need a model trained, I might be able to train a Res2NeXt v1b for you.
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Related Issues (20)
- tensorflow,keras预训练版本 HOT 2
- width = int(math.floor(planes * (baseWidth/64.0)))
- Can res2net have a basic block structure? HOT 6
- Res2Net object detection HOT 2
- 提供的Res2Net-v1b-50预训练模型与mmdetection不完全匹配
- 维度不匹配 HOT 2
- What is baseWidth? HOT 3
- About stype.stage HOT 3
- How to determine the width parameter HOT 1
- About ResNet18? HOT 3
- 张量尺寸不匹配问题 HOT 1
- why don't have the Res2Net-v1b-200-SSLD model code ? HOT 1
- 26是否可以替换成其他更小数值 HOT 2
- res2net50-v1b的训练策略 HOT 2
- About SSLD pretrained model HOT 3
- 对于每一个layer的第一个block,计算方式不是层级的,和论文中描述有差别 HOT 3
- Problem of Replacement of "BatchNorm" to "GroupNorm"
- self-supervised training on Imagenet
- 代码中的残差结构和图像中不一致 HOT 1
- Code Copyright Issues HOT 2
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