A systematic comparison of fine-tuning strategies for Stable Diffusion XL on 100k real SAR images finds that full UNet fine-tuning with LoRA text encoders and a learned <SAR> token gives the best generation quality.
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Quantitative Comparison of Fine-Tuning Techniques for Pretrained Latent Diffusion Models in the Generation of Unseen SAR Images
A systematic comparison of fine-tuning strategies for Stable Diffusion XL on 100k real SAR images finds that full UNet fine-tuning with LoRA text encoders and a learned <SAR> token gives the best generation quality.