| # Model Card for DuoduoCLIP | |
| 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). | |
| ***Note: We provide the main model in the initial release, we will soon upload the other models used in the paper.*** | |
| ## Model Details | |
| ### Model Description | |
| - **Finetuned from model:** OpenCLIP model ("ViT-B-32" architecture and checkpoint "laion2b_s34b_b79k") | |
| ### Model Sources | |
| - **Repository:** https://github.com/3dlg-hcvc/DuoduoCLIP | |
| - **Paper:** https://arxiv.org/abs/2406.11579 | |
| ### Model Checkpoints | |
| - **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. | |
| ## Training Data | |
| The dataset card can be found [here](https://huggingface.co/datasets/3dlg-hcvc/DuoduoCLIP-data). | |
| **BibTeX:** | |
| ```bibtex | |
| @misc{lee2024duoduo, | |
| title={Duoduo CLIP: Efficient 3D Understanding with Multi-View Images}, | |
| author={Han-Hung Lee and Yiming Zhang and Angel X. Chang}, | |
| year={2024}, | |
| eprint={2406.11579}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CV} | |
| } | |
| ``` | |
| ## Acknowledgement | |
| This work was funded by a CIFAR AI Chair, a NSERC Discovery grant, and a CFI/BCKDF JELF grant. |