Semantic Correspondence As An Optimal Transport Problem.pdf

Liu_Semantic_Correspondence_as_an_Optimal_Transport_Problem_CVPR_2020_paper.pdf
Preview of Semantic Correspondence as an Optimal Transport Problem
🔗 Source: openaccess.thecvf.com
📊 Size: 1.18 MB
👤 Author: Yanbin Liu, Linchao Zhu, Makoto Yamada, Yi Yang
⬇️ Downloads: 124

Summary

Establishing dense correspondences across semantically similar images is a challenging task due to large intra-class variation and background clutter, leading to two common issues: many-to-one matching and background matching. The proposed algorithm solves these issues by global feature matching, which maximizes total matching correlations between images, and applying a staircase function on class activation maps to re-weight pixel importance. The whole procedure is combined into a unified optimal transport algorithm, achieving state-of-the-art performance on four benchmark datasets with a 26% relative improvement on the SPair-71k dataset.

Description

Establishing dense correspondences across semantically similar images is a challenging task due to large intra-class variation and background clutter, leading...

Technical Information

  • File Format: PDF
  • File Size: 1.18 MB
  • Pages: 10
  • Language: EN
  • Author: Yanbin Liu, Linchao Zhu, Makoto Yamada, Yi Yang
  • Total Downloads: 124
  • Last Updated: 2 hours ago

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