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---
pipeline_tag: image-classification
tags:
- image-classification
license: mit
language:
- en
base_model:
- timm/vit_base_patch14_reg4_dinov2.lvd142m
---
# PdiscoFormer PartImageNet OOD Model (K=8)
PdiscoFormer (Vit-base-dinov2-reg4) trained on PartImageNet OOD with K (number of unsupervised parts to discover) set to a value of 8.
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
# BibTex entry and citation info
```
@misc{aniraj2024pdiscoformerrelaxingdiscoveryconstraints,
title={PDiscoFormer: Relaxing Part Discovery Constraints with Vision Transformers},
author={Ananthu Aniraj and Cassio F. Dantas and Dino Ienco and Diego Marcos},
year={2024},
eprint={2407.04538},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2407.04538},
}
``` |