Hudong Liu

CUEMP: Correspondence Uncertainty Estimation With Motion Priors for Dense Visual Odometry

Deep dense visual odometry has made significant advancements by leveraging dense flow fields. However, current mainstream flow-based visual odometry methods often fail to suppress the visual similarity noise in correlation volumes and rely on the inefficient four-scale pyramids for correlation sampl