arXiv:2610.00040v1 Announce Type: new
Abstract: Recent advances in 3D Gaussian Splatting have enabled open-vocabulary and referring segmentation by distilling semantic knowledge from 2D foundation mo...
By Thanh-Khoi Nguyen, Thien-Phuc Tran, Minh-Triet Tran
PointGauss is a 3D-native framework that performs semantic parsing and instance segmentation on 3D Gaussian splatting representations by treating Gaussian primitives as unstructured point sets and extracting scale‑invariant geometric features with Point Transformer V3. It introduces an adaptive region‑of‑interest cropping strategy and an instance‑aware distance‑constrained rasterization pipeline to enable scalable, view‑consistent pixel‑level projections. The authors also release SplatSeg‑360, a cross‑scale benchmark with 32 complex scenes and over 6,300 aligned 2D‑3D masks, and show that PointGauss achieves real‑time performance with state‑of‑the‑art 3D‑mIoU (~90%) and 2D‑mIoU (~80%) scores.
By Wentao Sun, Yiping Chen, John S. Zelek, Jonathan Li
GaussianDS introduces a depth‑supervised framework for 3D Gaussian Splatting that jointly optimizes RGB appearance, depth, and compact semantics from scratch. By arranging multi‑view images into a pose‑aware pseudo‑video and propagating view‑consistent masks via SAM2, the method aligns semantic lifting with geometric cues, using depth supervision and edge‑aware refinement to curb semantic drift and boundary leakage. The approach achieves state‑of‑the‑art performance on LERF and 3D‑OVS benchmarks while preserving high‑fidelity reconstruction and enabling downstream tasks such as 3D object removal.
By Yufei Zhang, Chenlu Zhan, Hongwei Wang
arXiv:2512. 23020v3 Announce Type: replace-cross Abstract: 3D visual grounding aims to locate objects based on natural language descriptions in 3D scenes.
By Wenyuan Huang, Zhenyu Zhang, Zhao Wang, Zhou Wei, Ting Huang, Fang Zhao, Jian Yang
arXiv:2606. 31148v1 Announce Type: cross Abstract: 3D Visual Grounding (3DVG) aims to localize target objects in 3D scenes given natural language descriptions.
By Duc Cao Dinh, Khai Le-Duc, Florent Draye, Chris Ngo, Terry Jingchen Zhang, Bernhard Sch\"olkopf, Zhijing Jin
ExtrinSplat is a new framework that separates geometry from semantics in 3D Gaussian Splatting scenes. It clusters Gaussians into overlapping 3D object groups and uses a Vision‑Language Model to generate lightweight textual hypotheses, creating an extrinsic index layer that handles complex polysemy. This approach reduces adaptation time from hours to minutes, cuts storage overhead by orders of magnitude, and outperforms existing embedding‑based methods on open‑vocabulary 3D object selection and semantic segmentation benchmarks.
By Jiayu Ding, Xinpeng Liu, Zhiyi Pan, Shiqiang Long, Ge Li