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.
Thanks for your amazing work!
But I have a probem about how to run code on MPII dataset.
As you mentioned in the code"BBox was added to the labels by the authors to perform additional training and testing, as referred in the paper."
Where can I get this?Can you provide the annotation file with BBox labels？ (TvT)
I would be appreciated if you can reply me.
JackZh4n9
commented
3 years ago
Thanks for your amazing work! But I have a probem about how to run code on MPII dataset. As you mentioned in the code"BBox was added to the labels by the authors to perform additional training and testing, as referred in the paper." Where can I get this?Can you provide the annotation file with BBox labels？ (TvT) I would be appreciated if you can reply me.