206 citations · 429 across the 7 of their papers we have counts for
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cs.CV2023★ 1 cited
Learning Content-enhanced Mask Transformer for Domain Generalized Urban-Scene Segmentation
Qi Bi, Shaodi You, Theo Gevers
Domain-generalized urban-scene semantic segmentation (USSS) aims to learn generalized semantic predictions across diverse urban-scene styles. Unlike domain gap challenges, USSS is…
cs.CV2023★ 206 cited
Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-world Applications
Wei Ji, Jingjing Li, Qi Bi +3
Recently, Meta AI Research approaches a general, promptable Segment Anything Model (SAM) pre-trained on an unprecedentedly large segmentation dataset (SA-1B). Without a doubt, the…