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`annotated_network.pth` is the pre-trained annotation network weights that can be used to
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annotate customized 3D object dataset. The detailed instruction is included [here](https://github.com/TCXX/ObjaversePlusPlus/blob/main/annotation_model/Readme.md).
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## Citation
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If you find this work useful for your research, please cite our paper:
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`annotated_network.pth` is the pre-trained annotation network weights that can be used to
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annotate customized 3D object dataset. The detailed instruction is included [here](https://github.com/TCXX/ObjaversePlusPlus/blob/main/annotation_model/Readme.md).
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## Dataset Evaluation
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We set up an image-to-3D generation task to evaluate our dataset using OpenLRM. We compared:
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- A randomly sampled subset of 100,000 objects from Objaverse (Training Set A)
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- A quality-filtered dataset of ~50,000 high-quality objects (Training Set B)
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Our key findings:
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- Better Generation Quality: User study shows significant preference for models trained on our curated dataset.
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- Faster Convergence: Our model demonstrates faster convergence on a carefully curated dataset.
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For more details, please read our [paper](https://arxiv.org/abs/2504.07334), which was peer reviewed at CVPR workshop (2025).
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## Citation
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If you find this work useful for your research, please cite our paper:
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