DADA: Depth-aware Domain Adaptation in Semantic Segmentation

ICCV 2019 Tuan-Hung VuHimalaya JainMaxime BucherMatthieu CordPatrick Pérez

Unsupervised domain adaptation (UDA) is important for applications where large scale annotation of representative data is challenging. For semantic segmentation in particular, it helps deploy on real "target domain" data models that are trained on annotated images from a different "source domain", notably a virtual environment... (read more)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT LEADERBOARD
Image-to-Image Translation SYNTHIA-to-Cityscapes DADA mIoU 42.6 # 9