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Models/DoG-BConvLSTM

DoG-BConvLSTM

Reported on 6 benchmarks across 3 tasks · 1 paper · 6 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology4 results

Few-Shot LearningonFSS-1000
Mean IoU· 2020-03-09
83.36
best: 87.8 (LSeg)
SOTA
On the Texture Bias for Few-Shot CNN Segmentation arXiv:2003.04052
Few-Shot LearningonPascal5i
meanIOU· 2020-03-09
60.6
best: 62.2 (A-MCG-Conv-LSTM)
SOTA
On the Texture Bias for Few-Shot CNN Segmentation arXiv:2003.04052
Meta-LearningonFSS-1000
Mean IoU· 2020-03-09
83.36
best: 87.8 (LSeg)
SOTA
On the Texture Bias for Few-Shot CNN Segmentation arXiv:2003.04052
Meta-LearningonPascal5i
meanIOU· 2020-03-09
60.6
best: 62.2 (A-MCG-Conv-LSTM)
SOTA
On the Texture Bias for Few-Shot CNN Segmentation arXiv:2003.04052

Computer Vision2 results

Few-Shot Semantic SegmentationonFSS-1000
Mean IoU· 2020-03-09
83.36
best: 87.8 (LSeg)
SOTA
On the Texture Bias for Few-Shot CNN Segmentation arXiv:2003.04052
Few-Shot Semantic SegmentationonPascal5i
meanIOU· 2020-03-09
60.6
best: 62.2 (A-MCG-Conv-LSTM)
SOTA
On the Texture Bias for Few-Shot CNN Segmentation arXiv:2003.04052