7 citations · 9 across the 3 of their papers we have counts for
3 papers
cs.CV2023
Weight-based Mask for Domain Adaptation
Eunseop Lee, Inhan Kim, Daijin Kim
In computer vision, unsupervised domain adaptation (UDA) is an approach to transferring knowledge from a label-rich source domain to a fully-unlabeled target domain. Conventional U…
cs.CV2022★ 2 cited
Object Discovery via Contrastive Learning for Weakly Supervised Object Detection
Jinhwan Seo, Wonho Bae, Danica J. Sutherland +2
Weakly Supervised Object Detection (WSOD) is a task that detects objects in an image using a model trained only on image-level annotations. Current state-of-the-art models benefit…
cs.CV2022★ 7 cited
Revisiting Image Pyramid Structure for High Resolution Salient Object Detection
Taehun Kim, Kunhee Kim, Joonyeong Lee +3
Salient object detection (SOD) has been in the spotlight recently, yet has been studied less for high-resolution (HR) images. Unfortunately, HR images and their pixel-level annotat…