Due to Marigold's generative nature, each prediction is unique and defined by the random noise sampled for the latent initialization.
This becomes an obvious drawback compared to traditional end-to-end dense regression networks, as exemplified in the following videos:  
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<img class="rounded-xl" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/marigold/marigold_obama.gif"/>