Fast SAM2 with Text-Driven Token Pruning
快速SAM2与文本驱动的标记剪枝
机构 * School of Computer Science and Engineering, University of Electronic Science and Technology of China(电子科技大学计算机科学与工程学院) ; Department of Computer Science and Engineering, Indian Institute of Technology, Delhi(印度理工学院德里分校计算机科学与工程系) ; School of Robotics and Advanced Manufacture, Harbin Institute of Technology(哈尔滨工业大学机器人与先进制造学院)
AI总结 本文提出文本驱动的标记剪枝方法,提升SAM2视频分割效率,实现推理速度提升42.50%和内存使用降低37.41%。
Comments 28 pages, 9 figures