DiLAST optimizes 3D latents via guidance from a 2D diffusion model to enable generalizable style transfer for OOD styles in 3D asset generation.
Plenoxels: Radiance fields without neural networks
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
HarmoGS adds semantic consistency-guided masking and dual-view orthogonal gradient harmonization to 3D Gaussian Splatting to reduce artifacts from distractors and cross-view illumination inconsistencies.
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Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion
DiLAST optimizes 3D latents via guidance from a 2D diffusion model to enable generalizable style transfer for OOD styles in 3D asset generation.
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HarmoGS: Robust 3D Gaussian Splatting in the Wild via Conflict-Aware Gradient Harmonization
HarmoGS adds semantic consistency-guided masking and dual-view orthogonal gradient harmonization to 3D Gaussian Splatting to reduce artifacts from distractors and cross-view illumination inconsistencies.