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arshafiee/hybridmqa-checkpoint
hybridmqa-checkpoint is a machine learning model from arshafiee. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This repository hosts the model weights for HybridMQA, a full-reference quality assessment method for 3D colored meshes. HybridMQA leverages both geometry and texture representations and models their interactions to p…
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Updated Jun 10, 2025
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From the Hugging Face model README
This repository hosts the model weights for HybridMQA, a full-reference quality assessment method for 3D colored meshes. HybridMQA leverages both geometry and texture representations and models their interactions to predict perceptual quality scores.
📄 Paper: arXiv:2412.01986
🌐 Project Page: https://arshafiee.github.io/hybridmqa/
💻 Codebase: GitHub Repository
This repository includes three trained HybridMQA checkpoints:
| Filename | Dataset | kfold_seed | shuffle_seed | Notes |
|---|---|---|---|---|
ckpt_TMQA_adapted.pth | TMQA | 27 | 0 | Trained on 80% with the given seeds |
ckpt_TSMD_adapted.pth | TSMD | 7 | 2 | Trained on 80% with the given seeds |
ckpt_YN2023_adapted.pth | YN2023 | 7 | 1 | Trained on 80% with the given seeds |
Download the checkpoint using:
from huggingface_hub import hf_hub_download
ckpt_path = hf_hub_download(
repo_id="arshafiee/hybridmqa-checkpoint",
filename="<checkpoint_name>.pth"
)
If you use this work in your research, please cite:
@InProceedings{sarvestani2025hybridmqa,
author = {Sarvestani, Armin Shafiee and Tang, Sheyang and Wang, Zhou},
title = {HybridMQA: Exploring Geometry-Texture Interactions for Colored Mesh Quality Assessment},
booktitle = {Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR)},
year = {2025},
pages = {21414-21424}
}
This model is released under the MIT License.