Langsplat: 3d language gaussian splatting

M Qin, W Li, J Zhou, H Wang… - Proceedings of the IEEE …, 2024‏ - openaccess.thecvf.com
Humans live in a 3D world and commonly use natural language to interact with a 3D scene.
Modeling a 3D language field to support open-ended language queries in 3D has gained …

Benchmarking neural radiance fields for autonomous robots: An overview

Y Ming, X Yang, W Wang, Z Chen, J Feng… - … Applications of Artificial …, 2025‏ - Elsevier
Abstract Neural Radiance Field (NeRF) has emerged as a powerful paradigm for scene
representation, offering high-fidelity renderings and reconstructions from a set of sparse and …

Garfield: Group anything with radiance fields

CM Kim, M Wu, J Kerr, K Goldberg… - Proceedings of the …, 2024‏ - openaccess.thecvf.com
Grou** is inherently ambiguous due to the multiple levels of granularity in which one can
decompose a scene---should the wheels of an excavator be considered separate or part of …

Semantically-aware neural radiance fields for visual scene understanding: A comprehensive review

TAQ Nguyen, A Bourki, M Macudzinski… - arxiv preprint arxiv …, 2024‏ - arxiv.org
This review thoroughly examines the role of semantically-aware Neural Radiance Fields
(NeRFs) in visual scene understanding, covering an analysis of over 250 scholarly papers. It …

EgoLifter: Open-World 3D Segmentation for Egocentric Perception

Q Gu, Z Lv, D Frost, S Green, J Straub… - European Conference on …, 2024‏ - Springer
In this paper we present EgoLifter, a novel system that can automatically segment scenes
captured from egocentric sensors into a complete decomposition of individual 3D objects …

N2f2: Hierarchical scene understanding with nested neural feature fields

Y Bhalgat, I Laina, JF Henriques, A Zisserman… - … on Computer Vision, 2024‏ - Springer
Understanding complex scenes at multiple levels of abstraction remains a formidable
challenge in computer vision. To address this, we introduce Nested Neural Feature Fields …

Omniseg3d: Omniversal 3d segmentation via hierarchical contrastive learning

H Ying, Y Yin, J Zhang, F Wang, T Yu… - Proceedings of the …, 2024‏ - openaccess.thecvf.com
Towards holistic understanding of 3D scenes a general 3D segmentation method is needed
that can segment diverse objects without restrictions on object quantity or categories while …

Sam-guided graph cut for 3d instance segmentation

H Guo, H Zhu, S Peng, Y Wang, Y Shen, R Hu… - … on Computer Vision, 2024‏ - Springer
This paper addresses the challenge of 3D instance segmentation by simultaneously
leveraging 3D geometric and multi-view image information. Many previous works have …

Panoptic vision-language feature fields

H Chen, K Blomqvist, F Milano… - IEEE Robotics and …, 2024‏ - ieeexplore.ieee.org
Recently, methods have been proposed for 3D open-vocabulary semantic segmentation.
Such methods are able to segment scenes into arbitrary classes based on text descriptions …

ClusteringSDF: Self-organized neural implicit surfaces for 3D decomposition

T Wu, C Zheng, Q Wu, TJ Cham - European Conference on Computer …, 2024‏ - Springer
Abstract 3D decomposition/segmentation remains a challenge as large-scale 3D annotated
data is not readily available. Existing approaches typically leverage 2D machine-generated …