activity
20242026
most citedReplaceAnything3D:Text-Guided 3D Scene Editing with Compositional Neural Radiance Fields

2 citations · 3 across the 5 of their papers we have counts for

collaborators

7 papers

cs.RO2026

Pandora: Articulated 3D Scene Graphs from Egocentric Vision

Alan Yu, Yun Chang, Christopher Xie +1

Robotic mapping systems typically approach building metric-semantic scene representations from the robot's own sensors and cameras. However, these "first person" maps inherit the r…

cs.CV2026

ReScene4D: Temporally Consistent Semantic Instance Segmentation of Evolving Indoor 3D Scenes

Emily Steiner, Jianhao Zheng, Henry Howard-Jenkins +2

Indoor environments evolve as objects move, appear, or leave the scene. Capturing these dynamics requires maintaining temporally consistent instance identities across intermittentl…

cs.GR2025

VertexRegen: Mesh Generation with Continuous Level of Detail

Xiang Zhang, Yawar Siddiqui, Armen Avetisyan +3

We introduce VertexRegen, a novel mesh generation framework that enables generation at a continuous level of detail. Existing autoregressive methods generate meshes in a partial-to…

cs.CV2025

Sonata: Self-Supervised Learning of Reliable Point Representations

Xiaoyang Wu, Daniel DeTone, Duncan Frost +7

In this paper, we question whether we have a reliable self-supervised point cloud model that can be used for diverse 3D tasks via simple linear probing, even with limited data and…

cs.CV2025

Human-in-the-Loop Local Corrections of 3D Scene Layouts via Infilling

Christopher Xie, Armen Avetisyan, Henry Howard-Jenkins +5

We present a novel human-in-the-loop approach to estimate 3D scene layout that uses human feedback from an egocentric standpoint. We study this approach through introduction of a n…

cs.CV2024★ 1 cited

SceneScript: Reconstructing Scenes With An Autoregressive Structured Language Model

Armen Avetisyan, Christopher Xie, Henry Howard-Jenkins +11

We introduce SceneScript, a method that directly produces full scene models as a sequence of structured language commands using an autoregressive, token-based approach. Our propose…

cs.CV2024★ 2 cited

ReplaceAnything3D:Text-Guided 3D Scene Editing with Compositional Neural Radiance Fields

Edward Bartrum, Thu Nguyen-Phuoc, Chris Xie +5

We introduce ReplaceAnything3D model (RAM3D), a novel text-guided 3D scene editing method that enables the replacement of specific objects within a scene. Given multi-view images o…