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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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- 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 Seg Model (K=50) |
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PdiscoFormer (Vit-base-dinov2-reg4) trained on PartImageNet Seg 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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} |
