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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: