Research map / Detection and segmentation / Open-set and few-shot detection
MCMC Shape Sampling for Image Segmentation With Nonparametric Shape Priors
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use MCMC shape sampling with nonparametric global shape priors instead of optimization-based segmentation | Aircraft segmentation · Aircraft test image set - 1 | F-measure | Helped |
| Use MCMC shape sampling with nonparametric global shape priors instead of optimization-based segmentation | Aircraft segmentation · Aircraft test image set - 2 | F-measure | Mixed |
| Use local rather than global shape priors (ablation) | MCMC shape sampling · Walking silhouettes | F-measure | Helped |
| Use global shape priors rather than Kim et al.'s optimization-based method | Walking silhouettes · Walking silhouettes | F-measure | Helped |
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- Learning Weight Uncertainty With Stochastic Gradient MCMC for Shape Classification (CVPR 2016 · similarity 0.85)
- Computing Valid P-Values for Image Segmentation by Selective Inference (CVPR 2020 · similarity 0.84)
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