Planar Ultrametric Rounding for Image Segmentation
We study the problem of hierarchical clustering on planar graphs. We formulate this in terms of an LP relaxation of ultrametric rounding. To solve this LP efficiently we introduce a dual cutting plane scheme that uses minimum cost perfect matching as a subroutine in order to efficiently explore the space of planar partitions. We apply our algorithm to the problem of hierarchical image segmentation.
Code (0)
등록된 구현이 없습니다.
Tasks
ClusteringImage SegmentationSegmentationSemantic SegmentationSimilar Papers 제목 키워드 기반
Planar Ultrametrics for Image Segmentation
We study the problem of hierarchical clustering on planar graphs. We formulate this in terms of finding the closest ultrametric to a specified set of distances and solve it using an LP relaxation that leverages minimum c…
ClusteringImage SegmentationSegmentationSemantic SegmentationView-Consistent Hierarchical 3D Segmentation Using Ultrametric Feature Fields
Large-scale vision foundation models such as Segment Anything (SAM) demonstrate impressive performance in zero-shot image segmentation at multiple levels of granularity. However, these zero-shot predictions are rarely 3D…
Image SegmentationNeRFSegmentationSemantic SegmentationImage Stitching Based on Planar Region Consensus
Image stitching for two images without a global transformation between them is notoriously difficult. In this paper, noticing the importance of planar structure under perspective geometry, we propose a new image stitchin…
Image StitchingSegmentationSemantic SegmentationUltrametric Component Analysis with Application to Analysis of Text and of Emotion
We review the theory and practice of determining what parts of a data set are ultrametric. It is assumed that the data set, to begin with, is endowed with a metric, and we include discussion of how this can be brought ab…
Next Generation Multicuts for Semi-Planar Graphs
We study the problem of multicut segmentation. We introduce modified versions of the Semi-PlanarCC based on bounding Lagrange multipliers. We apply our work to natural image segmentation.
Image SegmentationSegmentationSemantic Segmentation