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Published September 30, 2023 | Version v2

Rethinking pose estimation in crowds: overcoming the detection information bottleneck and ambiguity

  • 1. EPFL

Description

Here we provide neural networks weights for the best models in our article "Rethinking pose estimation in crowds: overcoming the detection information-bottleneck and ambiguity", ICCV 2023. Each model has the naming convention "dataset"-"modeltype".pth

The code to load and use the models is available at: https://github.com/amathislab/BUCTD

We also share the predictions from various bottom-up models to reproduce the training (as zip files). See our repository for more details.

Link to the article: https://openaccess.thecvf.com/content/ICCV2023/papers/Zhou_Rethinking_Pose_Estimation_in_Crowds_Overcoming_the_Detection_Information_Bottleneck_ICCV_2023_paper.pdf

 

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Files

coco.zip

Files (1.9 GB)

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md5:17b6323cae57357a1d34214d9f85532a
255.4 MB Download
md5:898a56e30d82671f4121c3a8531dea24
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463.5 MB Download
md5:b1874ba4ccfb403123f6bdf2f12d9c26
245.9 MB Preview Download
md5:17b6323cae57357a1d34214d9f85532a
255.4 MB Download
md5:3f9ca692ffaf5dd6ae1b59d5cb4c6809
21.3 MB Preview Download