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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ImportError: cannot import name 'ntid_data',我注意到utils模块下是没有ntid_data模块的,这个问题该怎么解决,谢谢 #34
Traceback (most recent call last):
File "unipose.py", line 12, in
from utils.utils import get_model_summary
File "/user3/lwx1055260/ID2463_UniPose_for_pytorch/utils/utils.py", line 8, in
from utils import ntid_data as ntid_data
ImportError: cannot import name 'ntid_data'
Traceback (most recent call last): File "unipose.py", line 12, in
from utils.utils import get_model_summary
File "/user3/lwx1055260/ID2463_UniPose_for_pytorch/utils/utils.py", line 8, in
from utils import ntid_data as ntid_data
ImportError: cannot import name 'ntid_data'