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README.md
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pipeline_tag: image-classification
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tags:
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---
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pipeline_tag: image-classification
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tags:
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- image-classification
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license: mit
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language:
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- en
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base_model:
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- timm/vit_base_patch14_reg4_dinov2.lvd142m
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# PdiscoFormer PartImageNet OOD Model (K=50)
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PdiscoFormer (Vit-base-dinov2-reg4) trained on PartImageNet OOD with K (number of unsupervised parts to discover) set to a value of 50.
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PdiscoFormer is a novel method for unsupervised part discovery using self-supervised Vision Transformers which achieves state-of-the-art results for this task, both qualitatively and quantitatively. The code can be found in the following repository: https://github.com/ananthu-aniraj/pdiscoformer
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# BibTex entry and citation info
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```
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@misc{aniraj2024pdiscoformerrelaxingdiscoveryconstraints,
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title={PDiscoFormer: Relaxing Part Discovery Constraints with Vision Transformers},
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author={Ananthu Aniraj and Cassio F. Dantas and Dino Ienco and Diego Marcos},
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year={2024},
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eprint={2407.04538},
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archivePrefix={arXiv},
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primaryClass={cs.CV},
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url={https://arxiv.org/abs/2407.04538},
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}
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```
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