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Roadmap of MMClassification #4

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hellock opened this issue Jul 13, 2020 · 11 comments
Open

Roadmap of MMClassification #4

hellock opened this issue Jul 13, 2020 · 11 comments

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@hellock
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@hellock hellock commented Jul 13, 2020

We keep this issue open to collect feature requests from users and hear your voice. Our monthly release plan is also available here.

You can either:

  1. Suggest a new feature by leaving a comment.
  2. Vote for a feature request with 馃憤 or be against with 馃憥. (Remember that developers are busy and cannot respond to all feature requests, so vote for your most favorable one!)
  3. Tell us that you would like to help implement one of the features in the list or review the PRs. (This is the greatest things to hear about!)
@GoldenAbel
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@GoldenAbel GoldenAbel commented Jul 16, 2020

warm up and more pretrained models

@LeeJZh
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@LeeJZh LeeJZh commented Jul 17, 2020

tricks like mix-up, auto-augmentation, and etc..

@Tshzzz
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@Tshzzz Tshzzz commented Jul 17, 2020

convert model to onnx.

@SilvioGiancola
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@SilvioGiancola SilvioGiancola commented Jul 20, 2020

EfficientNet, that could serve as backbone for mmdetection as well

@Ironteen
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@Ironteen Ironteen commented Jul 21, 2020

some Nerual Architecture Search algorithms which could be implement on one GPU, like ENAS

@soldier828
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@soldier828 soldier828 commented Jul 22, 2020

multi-brach for multi-task learning

@LeeJZh
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@LeeJZh LeeJZh commented Jul 23, 2020

convert model to onnx.

I think pytorch 1.5 supports it. torch.onnx

@GoldenAbel
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@GoldenAbel GoldenAbel commented Jul 28, 2020

darknet networks and data aug, like darknet53, mosaic, cutmix, mixup

@myopengit
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@myopengit myopengit commented Aug 4, 2020

benchmark on cifar10 and cifar100

@zhongqiu1245
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@zhongqiu1245 zhongqiu1245 commented Sep 20, 2020

Could you support HRNet?

@ousinkou
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@ousinkou ousinkou commented Oct 10, 2020

Multi-label classification

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