Vision Pretraining for Dense Spatial Perception

Researchers introduce a new vision pretraining method called masked boundary modeling, which improves dense spatial perception and depth estimation. This approach learns sub-pixel boundary representations and facilitates dense visual token learning. The method was used to develop LingBot-Vision, which shows enhanced performance in various vision tasks.

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