DOC-GS uses dual-domain calibration with continuous depth-guided dropout in optimization and dark channel prior evidence in observation to model and prune unreliable Gaussians, reducing haze and distortions in sparse-view 3DGS.
In Proceedings of the Computer Vision and Pattern Recognition Conference
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DOC-GS: Dual-Domain Observation and Calibration for Reliable Sparse-View Gaussian Splatting
DOC-GS uses dual-domain calibration with continuous depth-guided dropout in optimization and dark channel prior evidence in observation to model and prune unreliable Gaussians, reducing haze and distortions in sparse-view 3DGS.