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Found 2 papers, 2 papers with code
Benchmarking and Analysis of Unsupervised Object Segmentation from Real-world Single Images
We first introduce seven complexity factors to quantitatively measure the distributions of background and foreground object biases in appearance and geometry for datasets with human annotations.
Promising or Elusive? Unsupervised Object Segmentation from Real-world Single Images
We firstly introduce four complexity factors to quantitatively measure the distributions of object- and scene-level biases in appearance and geometry for datasets with human annotations.
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