2 citations · 4 across the 4 of their papers we have counts for
4 papers
VisDA 2022 Challenge: Domain Adaptation for Industrial Waste Sorting
Dina Bashkirova, Samarth Mishra, Diala Lteif +16
Label-efficient and reliable semantic segmentation is essential for many real-life applications, especially for industrial settings with high visual diversity, such as waste sortin…
CAFS: Class Adaptive Framework for Semi-Supervised Semantic Segmentation
Jingi Ju, Hyeoncheol Noh, Yooseung Wang +2
Semi-supervised semantic segmentation learns a model for classifying pixels into specific classes using a few labeled samples and numerous unlabeled images. The recent leading appr…
Bidirectional Domain Mixup for Domain Adaptive Semantic Segmentation
Daehan Kim, Minseok Seo, Kwanyong Park +4
Mixup provides interpolated training samples and allows the model to obtain smoother decision boundaries for better generalization. The idea can be naturally applied to the domain…
1st Place Solution to NeurIPS 2022 Challenge on Visual Domain Adaptation
Daehan Kim, Minseok Seo, YoungJin Jeon +1
The Visual Domain Adaptation(VisDA) 2022 Challenge calls for an unsupervised domain adaptive model in semantic segmentation tasks for industrial waste sorting. In this paper, we in…