A Mamba-based interactive state space model with cross-modal local scanning achieves competitive guided depth super-resolution performance at linear computational cost.
Ducos: Duality constrained depth super-resolution via foundation model
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LDCM achieves state-of-the-art metric depth completion from sparse observations by combining foundation-model initialization with a point-map regression head that removes the need for camera intrinsics.
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Interactive State Space Model with Cross-Modal Local Scanning for Depth Super-Resolution
A Mamba-based interactive state space model with cross-modal local scanning achieves competitive guided depth super-resolution performance at linear computational cost.
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Large Depth Completion Model from Sparse Observations
LDCM achieves state-of-the-art metric depth completion from sparse observations by combining foundation-model initialization with a point-map regression head that removes the need for camera intrinsics.