3 citations · 3 across the 4 of their papers we have counts for
3 papers · 1 filter
ARTA: Adaptive Mixed-Resolution Token Allocation for Efficient Dense Feature Extraction
David Hagerman, Roman Naeem, Erik Brorsson +2
We present ARTA, a mixed-resolution coarse-to-fine vision transformer for efficient dense feature extraction. Unlike models that begin with dense high-resolution (fine) tokens, ART…
MVUDA: Unsupervised Domain Adaptation for Multi-view Pedestrian Detection
Erik Brorsson, Lennart Svensson, Kristofer Bengtsson +1
We address multi-view pedestrian detection in a setting where labeled data is collected using a multi-camera setup different from the one used for testing. While recent multi-view…
ECAP: Extensive Cut-and-Paste Augmentation for Unsupervised Domain Adaptive Semantic Segmentation
Erik Brorsson, Knut Åkesson, Lennart Svensson +1
We consider unsupervised domain adaptation (UDA) for semantic segmentation in which the model is trained on a labeled source dataset and adapted to an unlabeled target dataset. Unf…