Official code for Anny-Fit: All-age Human Mesh Recovery accepted at CVPR 2026 Findings
Laura Bravo-Sánchez, Matthieu Armando, Romain Brégier, Grégory Rogez, Serena Yeung-Levy, Fabien Baradel
Our method recovers multi-person 3D human meshes from all ages directly in camera space. By integrating expert semantic, depth, keypoint, and segmentation cues, it improves all-age HMR and enables zero-shot adaptation of adult-only models.
- 206/05/05 — Code released
git clone --recurse-submodules https://github.com/naver/anny-fit
bash scripts/install.sh
bash scripts/download_checkpoints.sh
source setup.shSee INSTALL.md for details and troubleshooting tips.
Download the pre-processed demo data (images + preprocessing) for running Anny-Fit on sample images:
wget -O demo_data.tar.gz https://download.europe.naverlabs.com/ComputerVision/AnnyFit/demo_data.tar.gz
tar xzf demo_data.tar.gzOr run the preprocessing from scratch on a folder of images using a Multi-HMR 3D mesh initialization (requires all checkpoints):
python -m preprocess.build_test_dataset \
--data_root demo \
--dataset_name multi_person \
--preprocess_data \
--detector detectron2Visualize the preprocessing:
# Optional: visualize preprocessing for a random sample from a folder
python -m visualize.visualize_preprocessing --data_root demo -n 10
# Fitting with Anny-Fit:
cd annyfit
python optimize.py --config configs/demo/multihmr.yamlCode is provided under the terms of this LICENSE and accompanying NOTICE.
If you find our paper or code useful you can cite our work with:
@inproceedings{anny-fit2026,
title={Anny-Fit: All-age Human Mesh Recovery},
author={Bravo-S{\'a}nchez, Laura and
Armando, Matthieu and
Br{\'e}gier, Romain and
Rogez, Gr{\'e}gory and
Yeung-Levy, Serena and
Baradel, Fabien
},
booktitle={CVPR Findings},
year={2026}
}
Check out our other works that made this paper possible:
