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Synthetic-to-Real Translation
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Synthetic-to-real translation is the task of domain adaptation from synthetic (or virtual) data to real data.
<span style="color:grey; opacity: 0.6">( Image credit: CYCADA )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Learning Content-enhanced Mask Transformer for Domain Generalized Urban-Scene Segmentation
Hard-aware Instance Adaptive Self-training for Unsupervised Cross-domain Semantic Segmentation
MIC: Masked Image Consistency for Context-Enhanced Domain Adaptation
ELDA: Using Edges to Have an Edge on Semantic Segmentation Based UDA
PiPa: Pixel- and Patch-wise Self-supervised Learning for Domain Adaptative Semantic Segmentation
Deliberated Domain Bridging for Domain Adaptive Semantic Segmentation
CLUDA : Contrastive Learning in Unsupervised Domain Adaptation for Semantic Segmentation
Exploring High-quality Target Domain Information for Unsupervised Domain Adaptive Semantic Segmentation
HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation
ProCST: Boosting Semantic Segmentation Using Progressive Cyclic Style-Transfer
SePiCo: Semantic-Guided Pixel Contrast for Domain Adaptive Semantic Segmentation
Bidirectional Self-Training with Multiple Anisotropic Prototypes for Domain Adaptive Semantic Segmentation
Class-Balanced Pixel-Level Self-Labeling for Domain Adaptive Semantic Segmentation
Smoothing Matters: Momentum Transformer for Domain Adaptive Semantic Segmentation
Multiple Fusion Adaptation: A Strong Framework for Unsupervised Semantic Segmentation Adaptation
TridentAdapt: Learning Domain-invariance via Source-Target Confrontation and Self-induced Cross-domain Augmentation
DAFormer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation
SPCL: A New Framework for Domain Adaptive Semantic Segmentation via Semantic Prototype-based Contrastive Learning
Pixel-level Intra-domain Adaptation for Semantic Segmentation
Domain Adaptive Semantic Segmentation via Regional Contrastive Consistency Regularization
Unsupervised Domain Adaptation for Semantic Segmentation via Low-level Edge Information Transfer
Cross-Region Domain Adaptation for Class-level Alignment
Dual Path Learning for Domain Adaptation of Semantic Segmentation
Context-Aware Mixup for Domain Adaptive Semantic Segmentation
DSP: Dual Soft-Paste for Unsupervised Domain Adaptive Semantic Segmentation
Exploiting Image Translations via Ensemble Self-Supervised Learning for Unsupervised Domain Adaptation
Let's Play for Action: Recognizing Activities of Daily Living by Learning from Life Simulation Video Games
PixMatch: Unsupervised Domain Adaptation via Pixelwise Consistency Training
Contrastive Learning and Self-Training for Unsupervised Domain Adaptation in Semantic Segmentation
Self-supervised Augmentation Consistency for Adapting Semantic Segmentation
Domain Adaptive Semantic Segmentation with Self-Supervised Depth Estimation
Adaptive Boosting for Domain Adaptation: Towards Robust Predictions in Scene Segmentation
Coarse-to-Fine Domain Adaptive Semantic Segmentation with Photometric Alignment and Category-Center Regularization
MetaCorrection: Domain-aware Meta Loss Correction for Unsupervised Domain Adaptation in Semantic Segmentation
Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation
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