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Download the CUB Data

  1. Download CUB-200-2011 images.
wget http://www.vision.caltech.edu/visipedia-data/CUB-200-2011/CUB_200_2011.tgz && tar -xf CUB_200_2011.tgz
  1. Download our annotation files and pre-computed UV parameterization outputs. Do this from the csm_root/csm/ directory, and this should make csm_root/csm/cachedir directory. This also contains weights from the pretrained models.
wget https://cmu.box.com/s/goter3meyi7rssbh2rujg36dfwygnc3f && unzip cachedir.zip
Alternate link.
wget https://umich.box.com/s/nncgnzht90s9dnahodel116hgykmmf6o && unzip cachedir.zip

Computing the UV parameterization

Please read the instruction here to create the above parametrization if you would like to recompute here

Model Training

Train Birds

Without known pose

CODE_ROOT=/home/nileshk/csm_root/
cd $CODE_ROOT
python -m csm.experiments.csm.csp --name=csm_bird_net --n_data_workers=4 --dataset=cub  --display_port=8094 --scale_bias=0.75 --warmup_pose_iter=2000

With pose

CODE_ROOT=/home/nileshk/csm_root/
cd $CODE_ROOT
python -m csm.experiments.csm.csp --name=csm_bird_net_wpose --n_data_workers=4 --dataset=cub  --display_port=8094 --scale_bias=0.75 --multiple_cam_hypo=False --use_gt_quat=True --pred_cam=True

Train Cars

Without known pose

CODE_ROOT=/home/nileshk/csm_root/
cd $CODE_ROOT
python -m csm.experiments.csm.csp --name=csm_car_net --n_data_workers=4 --dataset=p3d --p3d_class=car  --display_port=8094 --scale_bias=1.0 --warmup_pose_iter=2000

With pose

CODE_ROOT=/home/nileshk/csm_root/
cd $CODE_ROOT
python -m csm.experiments.csm.csp --name=csm_car_net_wpose --n_data_workers=4 --dataset=p3d --p3d_class=car  --display_port=8094 --scale_bias=1.0 --multiple_cam_hypo=False --use_gt_quat=True --pred_cam=True --warmup_pose_iter=2000

Train on Imagenet Classes

Download Imagenet data here for categories in the paper.

imnet_class=horse
CODE_ROOT=/home/nileshk/csm_root/
cd $CODE_ROOT
python -m csm.experiments.csm.csp --name=csm_imnet_net_$imnet_class --n_data_workers=4 --dataset=imnet --imnet_class=$imnet_class  --display_port=8094 --scale_bias=1.0 --warmup_pose_iter=500