The code for CVPR 2025 paper "Reconstructing Close Human Interaction with Appearance and Proxemics Reasoning"
Buzhen Huang, Chen Li, Chongyang Xu, Dongyue Lu, Jinnan Chen, Yangang Wang, Gim Hee Lee
[Project] [Paper] [Dataset]
The code is tested on Ubuntu 22.04 with a single RTX 3090 GPU.
conda create -n closeapp python=3.10
pip install torch==2.3.0 torchvision==0.18.0 torchaudio==2.3.0 --index-url https://download.pytorch.org/whl/cu118
Then, compile diff-gaussian-rasterization as in 3DGS repository.
SDF loss and BVH_CUDA are required for evaluating penetration.
Download the official SMPL model from SMPL and SMPLify website and place them in data/smpl/smpl.
Download data from Baidu Netdisk or Google Drive.
python train.py -s data/preprocess_data/04305 -m output/04305 --train_stage=1 --save_render --use_appearance --save_params
If you find this code or dataset useful for your research, please consider citing the paper.
@inproceedings{huang2025reconstructing,
title={Reconstructing Close Human Interaction with Appearance and Proxemics Reasoning},
author={Huang, Buzhen and Li, Chen and Xu, Chongyang and Lu, Dongyue and Chen, Jinnan and Wang, Yangang and Lee, Gim Hee},
booktitle={Proceedings of the Computer Vision and Pattern Recognition Conference},
pages={17475--17485},
year={2025}
}
@inproceedings{huang2024closely,
title={Closely interactive human reconstruction with proxemics and physics-guided adaption},
author={Huang, Buzhen and Li, Chen and Xu, Chongyang and Pan, Liang and Wang, Yangang and Lee, Gim Hee},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={1011--1021},
year={2024}
}
Some of the code are based on the following works.
CloseInt
GaussianAvatar
aitviewer



