Qi Fan, Xin Tao, Lei Ke, Mingqiao Ye, Yuan Zhang...
TL;DR通过学习可变形偏移对图像特征进行采样来提高Segment Anything Model (SAM) 在各种情况下的分割稳定性,并验证了该方法的有效性和优势,从而使其成为更加稳健的分割解决方案。
Abstract
The segment anything model (sam) achieves remarkable promptable segmentation given high-quality prompts which, however, often require good skills to specify. To make →