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bmartacho / UniPose

We propose UniPose, a unified framework for human pose estimation, based on our “Waterfall” Atrous Spatial Pooling architecture, that achieves state-of-art-results on several pose estimation metrics. Current pose estimation methods utilizing standard CNN architectures heavily rely on statistical postprocessing or predefined anchor poses for joint localization. UniPose incorporates contextual seg- mentation and joint localization to estimate the human pose in a single stage, with high accuracy, without relying on statistical postprocessing methods. The Waterfall module in UniPose leverages the efficiency of progressive filter- ing in the cascade architecture, while maintaining multi- scale fields-of-view comparable to spatial pyramid config- urations. Additionally, our method is extended to UniPose- LSTM for multi-frame processing and achieves state-of-the- art results for temporal pose estimation in Video. Our re- sults on multiple datasets demonstrate that UniPose, with a ResNet backbone and Waterfall module, is a robust and efficient architecture for pose estimation obtaining state-of- the-art results in single person pose detection for both sin- gle images and videos.
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Questions about the augmentation on PennAction dataset #25

Open YHDang opened 3 years ago

YHDang commented 3 years ago

Hi, thanks for your excellent research. I'm confused about the data preprocessing on the PennAction. I see the TestResized() function is only used in utils.py, right? And why are not other augmentations used? Looking forward to your reply, thanks very much.

YuQi9797 commented 3 years ago

Hi, thanks for your excellent research. I'm confused about the data preprocessing on the PennAction. I see the TestResized() function is only used in utils.py, right? And why are not other augmentations used? Looking forward to your reply, thanks very much.

您好，请问关于作者的数据处理 penn_action_data.py 您调试成功了吗？ 我似乎不太明白作者本身对数据的分配是如何进行的，以及如何制作的dataloader，请问你能分享下你做的数据分配以及代码吗?

YHDang commented 3 years ago

您好，我是直接用的UniposeLSTM在PennAction上运行。但目前还没运行成功，遇到一个问题就是作者给的ground truth heatmap是368368，但模型的output是4646，很奇怪。

------------------ 原始邮件 ------------------ 发件人: @.>; 发送时间: 2021年6月14日(星期一) 中午1:56 收件人: @.>; 抄送: @.>; @.>; 主题: Re: [bmartacho/UniPose] Questions about the augmentation on PennAction dataset (#25)

您好，请问关于作者的数据处理 penn_action_data.py 您调试成功了吗？ 我似乎不太明白作者本身对数据的分配是如何进行的，以及如何制作的dataloader，请问你能分享下你做的数据分配以及代码吗?

— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub, or unsubscribe.

YuQi9797 commented 3 years ago

标签通过stride = 8， 变ground truth 变为46*46 所以就是46x46， 但是它的数据源数据是什么样的呢？ 能否分享下吗？

------------------ 原始邮件 ------------------ 发件人: @.>; 发送时间: 2021年6月15日(星期二) 上午8:39 收件人: @.>; 抄送: @.>; @.>; 主题: Re: [bmartacho/UniPose] Questions about the augmentation on PennAction dataset (#25)

您好，我是直接用的UniposeLSTM在PennAction上运行。但目前还没运行成功，遇到一个问题就是作者给的ground truth heatmap是368368，但模型的output是4646，很奇怪。

------------------ 原始邮件 ------------------ 发件人: @.>;
发送时间: 2021年6月14日(星期一) 中午1:56 收件人: @.>;
抄送: @.>; @.>;
主题: Re: [bmartacho/UniPose] Questions about the augmentation on PennAction dataset (#25)

您好，请问关于作者的数据处理 penn_action_data.py 您调试成功了吗？ 我似乎不太明白作者本身对数据的分配是如何进行的，以及如何制作的dataloader，请问你能分享下你做的数据分配以及代码吗?

— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub, or unsubscribe. — You are receiving this because you commented. Reply to this email directly, view it on GitHub, or unsubscribe.

YHDang commented 3 years ago

标签通过stride = 8， 变ground truth 变为46*46 所以就是46x46， 但是它的数据源数据是什么样的呢？ 能否分享下吗？ 我是直接用的作者给的那个dataloader，没做其他更改。