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Download the code
git clone --recursive https://github.com/shubhtuls/poseInduction
We first need to download the required datasets (PASCAL VOC and PASCAL3D+) and additional annotations. In addition, we also need to reorganize some data. To do this automatically, run
bash initSetup.sh
Edit the required paths in 'startup.m', specially if you've used a local copy of some data instead of downloading via initSetup.sh
Compile external/caffe (this is a slightly modified and outdated version of the original). Sample compilation instructions are provided below. In case of any issues, refer to the installation instructions on the caffe website.
cd external/caffe
cp Makefile.config.example Makefile.config
make -j 8
#edit MATLAB_DIR in Makefile.config
make matcaffe pycaffe
cd ../..
1) Demo
Initialize matlab in the root directory of the code.
Run
startup; demo();.
this will download our pretrained model and demonstrate predicted pose for a few images. Note that all the object classes in the demo images are novel (except for car which serves as a sanity check).
2) Training Models and Reproducing Experiments
This part of the codebase is still under construction. We'll update the instructions shortly.
About
Code release for "Pose Induction for Novel Object Categories", ICCV 2015.