Sketch2Pose: Estimating a 3D Character Pose from a Bitmap Sketch

Artists frequently capture character poses via raster sketches, then use these drawings as a reference while posing a 3D character in a specialized 3D software --- a time-consuming process, requiring specialized 3D training and mental effort. We tackle this challenge by proposing the first system for automatically inferring a 3D character pose from a single bitmap sketch, producing poses consistent with viewer expectations. Algorithmically interpreting bitmap sketches is challenging, as they contain significantly distorted proportions and foreshortening. We address this by predicting three key elements of a drawing, necessary to disambiguate the drawn poses: 2D bone tangents, self-contacts, and bone foreshortening. These elements are then leveraged in an optimization inferring the 3D character pose consistent with the artist's intent. Our optimization balances cues derived from artistic literature and perception research to compensate for distorted character proportions. We demonstrate a gallery of results on sketches of numerous styles. We validate our method via numerical evaluations, user studies, and comparisons to manually posed characters and previous work.

Project Page

Prerequisites

• GNU/Linux
• python
• pytorch
• [NVIDIA GPU] (optional, but highly recommended)

Download body model (SMPL-X)

Download SMPL-X body model from https://smpl-x.is.tue.mpg.de

See download.sh and run

sh ./scripts/download.sh

Virtual environement

Change pytorch version if needed in prepare.sh and run

sh ./scripts/prepare.sh

Demo

Activate virtual environement . venv/bin/activate and run

sh ./scripts/run.sh

# or

python src/pose.py \
        --save-path "${out_dir}" \
        --img-path "${img_path}" \
        --use-contacts \
        --use-natural \
        --use-cos \
        --use-angle-transf \

# or without contacts

python src/pose.py \
        --save-path "${out_dir}" \
        --img-path "${img_path}" \
        --use-natural \
        --use-cos \
        --use-angle-transf \

Citation

@article{brodt2022sketch2pose,
    author = {Kirill Brodt and Mikhail Bessmeltsev},
    title = {Sketch2Pose: Estimating a 3D Character Pose from a Bitmap Sketch},
    journal = {ACM Transactions on Graphics},
    year = {2022},
    month = {7},
    volume = {41},
    number = {4},
    doi = {10.1145/3528223.3530106},
}

Useful links

• Deep High-Resolution Representation Learning for Human Pose Estimation
• SMPLify-X (project)
• SPIN (project)
• eft
• SMPLify-XMC, selfcontact (project)
• Mixamo models with animations and a script to download them
• Quaternion-based Forward Kinematics