Yingcai Wan

You are already at the latest version Monocular Gaussian SLAM must recover camera motion, surface structure, and appearance from an RGB sequence without metric depth input or benchmark geometry during reconstruction. This setting is challenged by scale-ambiguous predictions, spatially varying reliability, and the tendency of an unconstrained Gaussian map to absorb pose and depth errors into its geometric and appearance parameters.

You are already at the latest version Monocular reconstruction under severe low light is ill-posed because underexposure removes repeatable texture, view-dependent camera processing violates photometric consistency, and pose or depth errors can be absorbed as blurred or distorted Gaussian primitives.

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