1.4k citations · 1.5k across the 18 of their papers we have counts for
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xMUDA: Cross-Modal Unsupervised Domain Adaptation for 3D Semantic Segmentation
Maximilian Jaritz, Tuan-Hung Vu, Raoul de Charette +2
Unsupervised Domain Adaptation (UDA) is crucial to tackle the lack of annotations in a new domain. There are many multi-modal datasets, but most UDA approaches are uni-modal. In th…
Zero-Shot Semantic Segmentation
Maxime Bucher, Tuan-Hung Vu, Matthieu Cord +1
Semantic segmentation models are limited in their ability to scale to large numbers of object classes. In this paper, we introduce the new task of zero-shot semantic segmentation:…
DADA: Depth-aware Domain Adaptation in Semantic Segmentation
Tuan-Hung Vu, Himalaya Jain, Maxime Bucher +2
Unsupervised domain adaptation (UDA) is important for applications where large scale annotation of representative data is challenging. For semantic segmentation in particular, it h…