1 citations · 1 across the 9 of their papers we have counts for
9 papers
FluSplat: Sparse-View 3D Editing without Test-Time Optimization
Haitao Huang, Shin-Fang Chng, Huangying Zhan +2
Recent advances in text-guided image editing and 3D Gaussian Splatting (3DGS) have enabled high-quality 3D scene manipulation. However, existing pipelines rely on iterative edit-an…
FAST3DIS: Feed-forward Anchored Scene Transformer for 3D Instance Segmentation
Changyang Li, Xueqing Huang, Shin-Fang Chng +3
While recent feed-forward 3D reconstruction models provide a strong geometric foundation for scene understanding, extending them to 3D instance segmentation typically relies on a d…
GRLoc: Geometric Representation Regression for Visual Localization
Changyang Li, Xuejian Ma, Lixiang Liu +3
Absolute Pose Regression (APR) has emerged as a compelling paradigm for visual localization. However, APR models typically operate as black boxes, directly regressing a 6-DoF pose…
RLGS: Reinforcement Learning-Based Adaptive Hyperparameter Tuning for Gaussian Splatting
Zhan Li, Huangying Zhan, Changyang Li +2
Hyperparameter tuning in 3D Gaussian Splatting (3DGS) is a labor-intensive and expert-driven process, often resulting in inconsistent reconstructions and suboptimal results. We pro…
ActiveGAMER: Active GAussian Mapping through Efficient Rendering
Liyan Chen, Huangying Zhan, Kevin Chen +4
We introduce ActiveGAMER, an active mapping system that utilizes 3D Gaussian Splatting (3DGS) to achieve high-quality, real-time scene mapping and exploration. Unlike traditional N…
Crafting Dynamic Virtual Activities with Advanced Multimodal Models
Changyang Li, Qingan Yan, Minyoung Kim +3
In this paper, we investigate the use of multimodal large language models (MLLMs) for generating virtual activities, leveraging the integration of vision-language modalities to ena…
NARUTO: Neural Active Reconstruction from Uncertain Target Observations
Ziyue Feng, Huangying Zhan, Zheng Chen +6
We present NARUTO, a neural active reconstruction system that combines a hybrid neural representation with uncertainty learning, enabling high-fidelity surface reconstruction. Our…
PlanarNeRF: Online Learning of Planar Primitives with Neural Radiance Fields
Zheng Chen, Qingan Yan, Huangying Zhan +7
Identifying spatially complete planar primitives from visual data is a crucial task in computer vision. Prior methods are largely restricted to either 2D segment recovery or simpli…
RIAV-MVS: Recurrent-Indexing an Asymmetric Volume for Multi-View Stereo
Changjiang Cai, Pan Ji, Qingan Yan +1
This paper presents a learning-based method for multi-view depth estimation from posed images. Our core idea is a "learning-to-optimize" paradigm that iteratively indexes a plane-s…