137 citations · 224 across the 13 of their papers we have counts for
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cs.CV2023
SEGIC: Unleashing the Emergent Correspondence for In-Context Segmentation
Lingchen Meng, Shiyi Lan, Hengduo Li +3
In-context segmentation aims at segmenting novel images using a few labeled example images, termed as "in-context examples", exploring content similarities between examples and the…
cs.CV2023★ 1 cited
BMB: Balanced Memory Bank for Imbalanced Semi-supervised Learning
Wujian Peng, Zejia Weng, Hengduo Li +1
Exploring a substantial amount of unlabeled data, semi-supervised learning (SSL) boosts the recognition performance when only a limited number of labels are provided. However, trad…