peterzs / ucmr

Code for the ECCV2020 paper "Shape and Viewpoint without Keypoints".

Shape and Viewpoints without Keypoints

Shubham Goel, Angjoo Kanazawa, Jitendra Malik

University of California, Berkeley In ECCV, 2020

Project Page

Requirements

• Python 3.7
• Pytorch 1.1.0
• Pymesh
• SoftRas
• NMR

Installation

Please use this Dockerfile to build your environment. For convenience, we provide a pre-built docker image at shubhamgoel/birds. If interested in a non-docker build, please follow docs/installation.md

Training

Please see docs/training.md

Demo

1. From the ucmr directory, download the pretrained models:

wget https://people.eecs.berkeley.edu/~shubham-goel/projects/ucmr/cub_train_cam4_withcam.tar.gz && tar -vzxf cub_train_cam4_withcam.tar.gz

You should see cachedir/snapshots/cam/e400_cub_train_cam4

2. Run the demo:

python -m src.demo \
    --pred_pose \
    --pretrained_network_path=cachedir/snapshots/cam/e400_cub_train_cam4/pred_net_600.pth \
    --shape_path=cachedir/template_shape/bird_template.npy\
    --img_path demo_data/birdie1.png

Evaluation

To evaluate camera poses errors on the entire test dataset, first download the CUB dataset and annotation files as instructed in docs/training.md. Then run

python -m src.experiments.benchmark \
        --pred_pose \
        --pretrained_network_path=cachedir/snapshots/cam/e400_cub_train_cam4/pred_net_600.pth \
        --shape_path=cachedir/template_shape/bird_template.npy \
        --nodataloader_computeMaskDt \
        --split=test

Citation

If you use this code for your research, please consider citing:

@inProceedings{ucmrGoel20,
  title={Shape and Viewpoints without Keypoints},
  author = {Shubham Goel and
  Angjoo Kanazawa and
  and Jitendra Malik},
  booktitle={ECCV},
  year={2020}
}

Acknowledgements

Parts of this code were borrowed from CMR and CSM.