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  ---
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  pipeline_tag: image-classification
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  tags:
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- - model_hub_mixin
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- - pytorch_model_hub_mixin
 
 
 
 
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  ---
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- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
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- - Library: https://github.com/ananthu-aniraj/pdiscoformer
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- - Docs: [More Information Needed]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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  ---
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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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+
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+ # BibTex entry and citation info
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+
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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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+ ```