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arXiv Computer Vision By Junfeng Ni, Zirui Zhou, Yixin Chen, Yu Liu, Nan Jiang, Zhifei Yang, Song-Chun Zhu, Siyuan Huang

DecomVoxel: Harnessing 3D-Native Priors with Guided In-situ Denoising Optimization for Decompositional Scene Reconstruction

Read the original on arXiv Computer Vision →

DecomVoxel introduces a guided in‑situ denoising optimization that fuses 3D‑native priors with neural scene reconstruction to improve decompositional scene reconstruction. The method employs an epsilon‑based distillation loss for stable latent refinement and adaptive spatial guidance using occupied and vacant anchors with temporal annealing to reduce hallucinations and spatial drift. Experiments on Replica and ScanNet++ demonstrate that DecomVoxel outperforms state‑of‑the‑art approaches while preserving spatial layout, structural fidelity, and style‑consistent texture, yielding high‑quality textured meshes with clean topology.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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