And since he read all these papers on this subject, which work did the biggest impression on him? “When I began research, I was really impressed by Marigold, which is the original model from our work. And that's why I really kind of pursued it and really tried to understand it,” Gonzalo explains. “I really like the idea of fine tuning these diffusion models to perform a non-generative task, more geometric or classical computer vision related tasks. For me, it's definitely Marigold!” A major lesson from this paper is that end-to-end fine-tuned diffusion models can be relatively simple. You can fine tune them on just one loss function, very standard loss functions and get very good results. Regarding future work, there is a lot of potential to introduce new loss functions, new losses and new tasks and really push this line of research. 10 DAILY WACV Saturday Oral Presentation
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