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cs.CV2025
Image Translation with Kernel Prediction Networks for Semantic Segmentation
Cristina Mata, Michael S. Ryoo, Henrik Turbell
Semantic segmentation relies on many dense pixel-wise annotations to achieve the best performance, but owing to the difficulty of obtaining accurate annotations for real world data…
cs.CV2025
CoPT: Unsupervised Domain Adaptive Segmentation using Domain-Agnostic Text Embeddings
Cristina Mata, Kanchana Ranasinghe, Michael S. Ryoo
Unsupervised domain adaptation (UDA) involves learning class semantics from labeled data within a source domain that generalize to an unseen target domain. UDA methods are particul…