Preprint
Jul 2026
Vision Pretraining for Dense Spatial Perception
This work proposes masked boundary modeling, a self-supervised paradigm that dynamically learns sub-pixel boundary representations and subsequently leverages the discovered boundary-bearing tokens as masked targets to facilitate dense visual token learning.
Zelin Fu, Bin Tan, Chang Sun et al.
· 3 citations
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