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Unsupervised Multiple Object Cosegmentation via Ensemble MIML Learning ... Object-Based Multiple Foreground Video Co-Segmentation via Multi-State Selection Graph.
To alleviate these limitations, we propose a novel unsupervised MFC framework, which is composed of three components: unsupervised label generation, saliency ...
Aug 20, 2020 · To alleviate these limitations, we propose a novel unsupervised MFC framework, which is composed of three components: unsupervised label ...
Multi-class co-segmentation is a challenging task because of the variety and complexity of the objects and images. To get more accurate object proposals is ...
Abstract: As an interesting and emerging topic, multiple foreground cosegmentation (MFC) aims at extracting a finite number of common objects from an image ...
Unsupervised Multiple Object Cosegmentation via Ensemble MIML Learning ... Learning Discriminative Feature with CRF for Unsupervised Video Object Segmentation.
... Segmentation via Prototype-based Pseudo-labeling and Contrastive Learning ... Object Tracking and Its Real-world Deployment via Reinforcement Learning.
In the paper, we propose an algorithm for simultaneously localizing objects and discovering object classes via bottom-up (saliency-guided) multiple class ...
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Dec 11, 2016 · Multiple instance learning (MIL) is a form of weakly supervised learning where training instances are arranged in sets, called bags, ...
In traditional multi-instance learning (MIL), instances are typically represented by using a single feature view. As MIL becoming popular in domain specific ...