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Joint Viewpoint & Keypoint estimation with CNNs (Caffe)

Paper (oral) GCPR 2019: https://arxiv.org/pdf/1912.06274.pdf

supp. material: http://pages.iai.uni-bonn.de/gall_juergen/download/kp-vpi_supp.pdf

Models

Models Keypoint + Viewpont Estimation (Caffe):

  • ObjectNet3D - KP+VP Real Data

https://drive.google.com/file/d/1ZdF6RZUkUrtf7yfvnt8L-_CmK58nyvv7/view?usp=sharing

  • ObjectNet3D - KP+VP Real + Synthetic (ShapeNet+Own) Data

https://drive.google.com/file/d/11Njc2Z8W3jzQg8428LXj1unIjLFtfFOZ/view?usp=sharing

Models Viewpoint Estimation Only (Caffe):

  • ObjectNet3D - Classication Real Data

https://drive.google.com/file/d/1BdUan6iMjUm-o4m8gLKK71RWwNTPYJMy/view?usp=sharing

  • ObjectNet3D - Classification Real + Synthetic (ShapeNet+Own) Data

https://drive.google.com/file/d/1WrJzm5MWVpdvVgutbQ-zOMrWa2TJys5W/view?usp=sharing

  • Pascal3D - Classication Real Data

https://drive.google.com/file/d/13iu9UOGRIEOtZPV3-RLHXGEHiFXlDgFA/view?usp=sharing

  • Pascal3D - Classification Real + Synthetic (ShapeNet+Own) Data

https://drive.google.com/file/d/1VLKK_mRmVn3tYygJBwmBEikdpeaxeXUK/view?usp=sharing

How to set-up the CNN framework
  • Caffe-git is an enhanced copy of Caffe version github on Dec 2016

Source: https://drive.google.com/file/d/1FjJcTY8x4lxyk_ErZIto9O52uaD62OsR/view?usp=sharing

  • The given VS2013 should be working straight forward

Binaries: https://drive.google.com/file/d/1IcQJGt6U_fxJzkD2q2lm9bqzmPwP1nUy/view?usp=sharing

  • caffe.mexw64 for matlab found here: ~/features/CNN/
Requirements
  • Matlab (tested on version 2013a)
  • Cygwin terminal for running the trainings
  • Python 2.7.1X
Setup, train and test models (Windows)
  • Training: Create models to be trained (matlab):
    • have a look at main_pose_train.m, based on InputParameters.m, the core function
    • cpm = only keypoint estimation, vp = only viewpoint and cpm-vp = joint trainingTrain a model:
    • Open a cygwin (a cmd promp should work as well, although it might crashed right after the first training, in case you have a sequence of models to be trained in a .sh file. 
    • The generated models to be trained (solver.prototxt, traintest.prototxt will be called from "./train.sh".
  • Test those models:
    • Follow Run_Pose and modify the 2 main functions: main_pose_test.m and poseEstimation.m if necessary. They are also based on InputParameters.m
Usage of synthetic data
Datasets

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CNN Network with joint real and synthetic data for viewpoint and keypoint estimation

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