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Datasets/PASCAL-5i

PASCAL-5i

ImagesUnknownIntroduced 2017-01-01

PASCAL-5i is a dataset used to evaluate few-shot segmentation. The dataset is sub-divided into 4 folds each containing 5 classes. A fold contains labelled samples from 5 classes that are used for evaluating the few-shot learning method. The rest 15 classes are used for training.

Source: AMP: Adaptive Masked Proxies for Few-Shot Segmentation Image Source: https://arxiv.org/pdf/1709.03410.pdf

Related Benchmarks

PASCAL-5i (1-Shot)/Few-Shot Learning/FB-IoUPASCAL-5i (1-Shot)/Few-Shot Learning/Mean Base and NovelPASCAL-5i (1-Shot)/Few-Shot Learning/Mean IoUPASCAL-5i (1-Shot)/Few-Shot Learning/learnable parameters (million)PASCAL-5i (1-Shot)/Few-Shot Semantic Segmentation/FB-IoUPASCAL-5i (1-Shot)/Few-Shot Semantic Segmentation/Mean Base and NovelPASCAL-5i (1-Shot)/Few-Shot Semantic Segmentation/Mean IoUPASCAL-5i (1-Shot)/Few-Shot Semantic Segmentation/learnable parameters (million)PASCAL-5i (1-Shot)/Meta-Learning/FB-IoUPASCAL-5i (1-Shot)/Meta-Learning/Mean Base and NovelPASCAL-5i (1-Shot)/Meta-Learning/Mean IoUPASCAL-5i (1-Shot)/Meta-Learning/learnable parameters (million)PASCAL-5i (10-Shot)/Few-Shot Learning/Mean IoUPASCAL-5i (10-Shot)/Few-Shot Semantic Segmentation/Mean IoUPASCAL-5i (10-Shot)/Meta-Learning/Mean IoUPASCAL-5i (5-Shot)/Few-Shot Learning/FB-IoUPASCAL-5i (5-Shot)/Few-Shot Learning/Mean Base and NovelPASCAL-5i (5-Shot)/Few-Shot Learning/Mean IoUPASCAL-5i (5-Shot)/Few-Shot Learning/learnable parameters (million)PASCAL-5i (5-Shot)/Few-Shot Semantic Segmentation/FB-IoUPASCAL-5i (5-Shot)/Few-Shot Semantic Segmentation/Mean Base and NovelPASCAL-5i (5-Shot)/Few-Shot Semantic Segmentation/Mean IoUPASCAL-5i (5-Shot)/Few-Shot Semantic Segmentation/learnable parameters (million)PASCAL-5i (5-Shot)/Meta-Learning/FB-IoUPASCAL-5i (5-Shot)/Meta-Learning/Mean Base and NovelPASCAL-5i (5-Shot)/Meta-Learning/Mean IoUPASCAL-5i (5-Shot)/Meta-Learning/learnable parameters (million)

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Few-Shot LearningFew-Shot Semantic SegmentationSemantic Segmentation