ILM-ASSL

Reported on 2 benchmarks across 1 task · 1 paper · 2 SOTA

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

Methodology2 results

Domain AdaptationonSYNTHIA-to-Cityscapes
mIoU· 2023-01-31
76.6
best: 78.1 (HALO)
SOTA
Iterative Loop Method Combining Active and Semi-Supervised Learning for Domain Adaptive Semantic Segmentation arXiv:2301.13361
Domain AdaptationonGTA5 to Cityscapes
mIoU· uses extra data· 2023-01-31
76.1
best: 77.8 (HALO)
SOTA
Iterative Loop Method Combining Active and Semi-Supervised Learning for Domain Adaptive Semantic Segmentation arXiv:2301.13361