AdapNet++

Reported on 6 benchmarks across 2 tasks · 1 paper

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

Medical3 results

Semantic SegmentationonScanNetV2
Mean IoU· 2018-08-11
50.3
best: 57.7 (SSMA)
Self-Supervised Model Adaptation for Multimodal Semantic Segmentation arXiv:1808.03833
Semantic SegmentationonSYNTHIA-CVPR’16
Mean IoU· 2018-08-11
87.87
best: 92.1 (SSMA)
Self-Supervised Model Adaptation for Multimodal Semantic Segmentation arXiv:1808.03833
Semantic SegmentationonFreiburg Forest
Mean IoU· 2018-08-11
83.09
best: 84.18 (SSMA)
Self-Supervised Model Adaptation for Multimodal Semantic Segmentation arXiv:1808.03833

Audio3 results

10-shot image generationonScanNetV2
Mean IoU· 2018-08-11
50.3
best: 57.7 (SSMA)
Self-Supervised Model Adaptation for Multimodal Semantic Segmentation arXiv:1808.03833
10-shot image generationonSYNTHIA-CVPR’16
Mean IoU· 2018-08-11
87.87
best: 92.1 (SSMA)
Self-Supervised Model Adaptation for Multimodal Semantic Segmentation arXiv:1808.03833
10-shot image generationonFreiburg Forest
Mean IoU· 2018-08-11
83.09
best: 84.18 (SSMA)
Self-Supervised Model Adaptation for Multimodal Semantic Segmentation arXiv:1808.03833