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- ---
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- license: cc
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: cc
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+ language:
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+ - en
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+ tags:
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+ - self-supervised
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+ - diffusion models
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+ - mocov3
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+ - simclrv2
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+ - dino
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+ - x-rays
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+ - landmark detection
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+ ---
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+
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+
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+ # Official PyTorch pre-trained models of the paper: "Self-supervised pre-training with diffusion model for few-shot landmark detection in x-ray images" (WACV 2025)
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+
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+
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+ The models available include:
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+
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+ - Our DDPM pre-trained model at 6k, 8k, 8k iterations respectively for the Chest, Cephalometric and Hand dataset
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+ - MocoV3 densenet161 model at 10k iterations for the Chest, Cephalometric and Hand dataset
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+ - SimClrV2 densenet161 model at 10k iterations for the Chest, Cephalometric and Hand dataset
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+ - Dino densenet161 model at 10k iterations for the Chest, Cephalometric and Hand dataset
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+
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+
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+ # Citation
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+
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+ Accepted at WACV (Winter Conference on Applications of Computer Vision) 2025.
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+
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+ ### Bibtex
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+
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+ ```
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+ @article{DiVia2024,
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+ author = {Di Via, R. and Odone, F. and Pastore, V. P.},
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+ title = {Self-supervised pre-training with diffusion model for few-shot landmark detection in x-ray images},
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+ year = {2024},
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+ journal = {arXiv},
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+ volume = {2407.18125},
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+ url = {https://arxiv.org/abs/2407.18125},
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+ note = {Submitted on 25 Jul 2024 (v1), last revised 29 Oct 2024 (this version, v2)}
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+ }
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+ ```
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+
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+ ### APA
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+
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+ ```
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+ Di Via, R., Odone, F., & Pastore, V. P. (2024). Self-supervised pre-training with diffusion model for few-shot landmark detection in x-ray images. ArXiv. https://arxiv.org/abs/2407.18125
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+ ```