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.
d 2gs: Depth- and-density guided gaussian splatting for stable and accurate sparse-view reconstruction
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
PairDropGS uses paired dropout with low-frequency consistency regularization and progressive scheduling to stabilize and improve sparse-view 3D Gaussian Splatting.
citing papers explorer
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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.
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PairDropGS: Paired Dropout-Induced Consistency Regularization for Sparse-View Gaussian Splatting
PairDropGS uses paired dropout with low-frequency consistency regularization and progressive scheduling to stabilize and improve sparse-view 3D Gaussian Splatting.