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开源软件名称:densepose开源软件地址:https://gitee.com/Yang_Feng1/densepose开源软件介绍:DensePose:Dense Human Pose Estimation In The Wild Rıza Alp Güler, Natalia Neverova, Iasonas Kokkinos [ Dense human pose estimation aims at mapping all human pixels of an RGB image to the 3D surface of the human body.DensePose-RCNN is implemented in the Detectron framework and is powered by Caffe2. In this repository, we provide the code to train and evaluate DensePose-RCNN. We also provide notebooks to visualize the collected DensePose-COCO dataset and show the correspondences to the SMPL model. Important Note!!! This project is no longer supported !!! DensePose is now part of Detectron2 (https://github.com/facebookresearch/detectron2/tree/master/projects/DensePose). There you can find the most up to date architectures / models. If you think some feature is missing from there, please post an issue in Detectron2 DensePose. InstallationPlease find installation instructions for Caffe2 and DensePose in Inference-Training-TestingAfter installation, please see NotebooksVisualization of DensePose-COCO annotations:See DensePose-COCO in 3D:See Visualize DensePose-RCNN Results:See DensePose-RCNN Texture Transfer:See LicenseThis source code is licensed under the license found in the Citing DensePoseIf you use Densepose, please use the following BibTeX entry. @InProceedings{Guler2018DensePose, title={DensePose: Dense Human Pose Estimation In The Wild}, author={R\{i}za Alp G\"uler, Natalia Neverova, Iasonas Kokkinos}, journal={The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year={2018} } |
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