Abstract: Automatic medical image segmentation has witnessed significant development with the success of large models on massive datasets. However, acquiring and annotating vast medical image datasets ...
Abstract: Semantic segmentation is a fundamental task in computer vision, and it has various applications in fields such as robotic sensing, video surveillance, and autonomous driving. A major ...
GroupViT is a framework for learning semantic segmentation purely from text captions without using any mask supervision. It learns to perform bottom-up heirarchical spatial grouping of ...
Abstract: Recently, CLIP has been applied to pixel-level zero-shot learning tasks via a two-stage scheme. The general idea is to first generate class-agnostic region proposals and then feed the ...
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