# Constrained Dominant sets and Its applications in computer vision

arXiv: https://arxiv.org/abs/2002.06028 · HTML: https://mlsanity.com/paper/2002.06028/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Feb 2020.

## Built on by (most cited first, 2 of 2)

- [Accelerating SfM-based Pose Estimation with Dominating Set](https://mlsanity.com/paper/2506.03667/) (2025)
- [An Adaptor for Triggering Semi-Supervised Learning to Out-of-Box Serve Deep Image Clustering](https://mlsanity.com/paper/2509.20976/) (2025)

## Abstract (arXiv)

In this thesis, we present new schemes which leverage a constrained clustering method to solve several computer vision tasks ranging from image retrieval, image segmentation and co-segmentation, to person re-identification. In the last decades clustering methods have played a vital role in computer vision applications; herein, we focus on the extension, reformulation, and integration of a well-known graph and game theoretic clustering method known as Dominant Sets. Thus, we have demonstrated the validity of the proposed methods with extensive experiments which are conducted on several benchmark datasets.