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Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Paper Title
MIC75.9MIC: Masked Image Consistency for Context-Enhanced Domain Adaptation
HRDA + PiPa75.6PiPa: Pixel- and Patch-wise Self-supervised Learning for Domain Adaptative Semantic Segmentation
HRDA73.8HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation
DAFormer + PiPa71.7PiPa: Pixel- and Patch-wise Self-supervised Learning for Domain Adaptative Semantic Segmentation
SePiCo70.3SePiCo: Semantic-Guided Pixel Contrast for Domain Adaptive Semantic Segmentation
CAMix (w DAFormer)70.0Context-Aware Mixup for Domain Adaptive Semantic Segmentation
DAFormer + ProCST69.4ProCST: Boosting Semantic Segmentation Using Progressive Cyclic Style-Transfer
DAFormer68.3DAFormer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation
TransDA-B63.9Smoothing Matters: Momentum Transformer for Domain Adaptive Semantic Segmentation
DDB62.7Deliberated Domain Bridging for Domain Adaptive Semantic Segmentation
EHTDI*62.0Exploring High-quality Target Domain Information for Unsupervised Domain Adaptive Semantic Segmentation
CPSL60.8Class-Balanced Pixel-Level Self-Labeling for Domain Adaptive Semantic Segmentation
G2L59.7G2L: A Global to Local Alignment Method for Unsupervised Domain Adaptive Semantic Segmentation
ProDA+CRA58.6Cross-Region Domain Adaptation for Class-level Alignment
ProDA57.5Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation
CAMix (w Deeplabv2 ResNet 101)55.2Context-Aware Mixup for Domain Adaptive Semantic Segmentation
CCM49.9Content-Consistent Matching for Domain Adaptive Semantic Segmentation
CBST47.0Unsupervised Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training
ADVENT44.8ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation
ResNet101 65.141.7Deep Residual Learning for Image Recognition
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