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A simple image segmentation framework via in-context examples
Recently, there have been explorations of generalist segmentation models that can
effectively tackle a variety of image segmentation tasks within a unified in-context learning …
effectively tackle a variety of image segmentation tasks within a unified in-context learning …
Unleashing the potential of the diffusion model in few-shot semantic segmentation
The Diffusion Model has not only garnered noteworthy achievements in the realm of image
generation but has also demonstrated its potential as an effective pretraining method …
generation but has also demonstrated its potential as an effective pretraining method …
Balancing the Scales: A Theoretical and Algorithmic Framework for Learning from Imbalanced Data
Class imbalance remains a major challenge in machine learning, especially in multi-class
problems with long-tailed distributions. Existing methods, such as data resampling, cost …
problems with long-tailed distributions. Existing methods, such as data resampling, cost …