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Optimizing Edge Detection for Image Segmentation with Multicut Penalties
The Minimum Cost Multicut Problem (MP) is a popular way for obtaining a graph decomposition by optimizing binary edge labels over edge costs.
Uncertainty in Minimum Cost Multicuts for Image and Motion Segmentation
The minimum cost lifted multicut approach has proven practically good performance in a wide range of applications such as image decomposition, mesh segmentation, multiple object tracking, and motion segmentation.
Self-supervised Sparse to Dense Motion Segmentation
We evaluate our method on the well-known motion segmentation datasets FBMS59 and DAVIS16.
Object Segmentation Tracking from Generic Video Cues
Our simple method can provide competitive results compared to the costly CNN-based methods with parameter tuning.
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