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Found 3 papers, 1 papers with code
Deep Constrained Dominant Sets for Person Re-identification
By optimizing the constrained clustering in an end-to-end manner, we naturally leverage the contextual knowledge of a set of images corresponding to the given person-images.
Ranked #2 on
Person Re-Identification
on CUHK03
(Rank-5 metric)
Multi-feature Fusion for Image Retrieval Using Constrained Dominant Sets
In this paper, we propose a computationally efficient approach to fuse several hand-crafted and deep features, based on the probabilistic distribution of a given membership score of a constrained cluster in an unsupervised manner.
Dominant Sets for "Constrained" Image Segmentation
In particular, we shall focus on interactive segmentation and co-segmentation (in both the unsupervised and the interactive versions).
