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| # Model Card for DuoduoCLIP |
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| In this model repo we provide the official pretrained models used in the paper **Duoduo CLIP: Efficient 3D Understanding with Multi-View Images.** |
| The model usage and code can be found in the [github repo](https://github.com/3dlg-hcvc/DuoduoCLIP). |
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| ***Note: We provide the main model in the initial release, we will soon upload the other models used in the paper.*** |
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| ## Model Details |
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| ### Model Description |
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| - **Finetuned from model:** OpenCLIP model ("ViT-B-32" architecture and checkpoint "laion2b_s34b_b79k") |
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| ### Model Sources |
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| - **Repository:** https://github.com/3dlg-hcvc/DuoduoCLIP |
| - **Paper:** https://arxiv.org/abs/2406.11579 |
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| ### Model Checkpoints |
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| - **Four_1to6F_bs1600_LT6.ckpt:** The model trained with the Four dataset and 1 to 6 frames sampled during training, with the last 6 attention layers trainable. |
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| ## Training Data |
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| The dataset card can be found [here](https://huggingface.co/datasets/3dlg-hcvc/DuoduoCLIP-data). |
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| **BibTeX:** |
| ```bibtex |
| @inproceedings{ |
| lee2025duoduo, |
| title={Duoduo {CLIP}: Efficient 3D Understanding with Multi-View Images}, |
| author={Han-Hung Lee and Yiming Zhang and Angel X Chang}, |
| booktitle={The Thirteenth International Conference on Learning Representations}, |
| year={2025}, |
| url={https://openreview.net/forum?id=iGbuc9ekKK} |
| } |
| ``` |
| |
| ## Acknowledgement |
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| This work was funded by a CIFAR AI Chair, an NSERC Discovery grant, and a CFI/BCKDF JELF grant. |
