Semi-Supervised RGBD Semantic Segmentation
2 papers with code • 1 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Semi-Supervised RGBD Semantic Segmentation
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
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2D-3D-S
Most implemented papers
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
CuriousAI/mean-teacher
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NeurIPS 2017
Without changing the network architecture, Mean Teacher achieves an error rate of 4. 35% on SVHN with 250 labels, outperforming Temporal Ensembling trained with 1000 labels.
Missing Modality Robustness in Semi-Supervised Multi-Modal Semantic Segmentation
harshm121/m3l
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We create the first benchmark for semi-supervised multi-modal semantic segmentation and also report the robustness to missing modalities.
