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Found 4 papers, 4 papers with code
A Simple Recipe for Language-guided Domain Generalized Segmentation
Generalization to new domains not seen during training is one of the long-standing challenges in deploying neural networks in real-world applications.
PODA: Prompt-driven Zero-shot Domain Adaptation
In this paper, we propose the task of 'Prompt-driven Zero-shot Domain Adaptation', where we adapt a model trained on a source domain using only a general description in natural language of the target domain, i. e., a prompt.
PØDA: Prompt-driven Zero-shot Domain Adaptation
In this paper, we propose the task of `Prompt-driven Zero-shot Domain Adaptation', where we adapt a model trained on a source domain using only a general description in natural language of the target domain, i. e., a prompt.
Unrolling PALM for sparse semi-blind source separation
Sparse Blind Source Separation (BSS) has become a well established tool for a wide range of applications - for instance, in astrophysics and remote sensing.
