activity
20232026
most citedBridge 2D-3D: Uncertainty-aware Hierarchical Registration Network with Domain Alignment

5 citations · 8 across the 13 of their papers we have counts for

collaborators

14 papers

cs.CV2026

ReFlow: Self-correction Motion Learning for Dynamic Scene Reconstruction

Yanzhe Liang, Ruijie Zhu, Hanzhi Chang +3

We present ReFlow, a unified framework for monocular dynamic scene reconstruction that learns 3D motion in a novel self-correction manner from raw video. Existing methods often suf…

cs.CV2026

GLASS: Geometry-aware Local Alignment and Structure Synchronization Network for 2D-3D Registration

Zhixin Cheng, Jiacheng Deng, Xinjun Li +5

Image-to-point cloud registration methods typically follow a coarse-to-fine pipeline, extracting patch-level correspondences and refining them into dense pixel-to-point matches. Ho…

cs.CV2026

GeoGuide: Hierarchical Geometric Guidance for Open-Vocabulary 3D Semantic Segmentation

Xujing Tao, Chuxin Wang, Yubo Ai +8

Open-vocabulary 3D semantic segmentation aims to segment arbitrary categories beyond the training set. Existing methods predominantly rely on distilling knowledge from 2D open-voca…

cs.CV2025★ 5 cited

Bridge 2D-3D: Uncertainty-aware Hierarchical Registration Network with Domain Alignment

Zhixin Cheng, Jiacheng Deng, Xinjun Li +2

The method for image-to-point cloud registration typically determines the rigid transformation using a coarse-to-fine pipeline. However, directly and uniformly matching image patch…

cs.CV2025

SAS: Segment Any 3D Scene with Integrated 2D Priors

Zhuoyuan Li, Jiahao Lu, Jiacheng Deng +4

The open vocabulary capability of 3D models is increasingly valued, as traditional methods with models trained with fixed categories fail to recognize unseen objects in complex dyn…

cs.CV2025

Beyond the Final Layer: Hierarchical Query Fusion Transformer with Agent-Interpolation Initialization for 3D Instance Segmentation

Jiahao Lu, Jiacheng Deng, Tianzhu Zhang

3D instance segmentation aims to predict a set of object instances in a scene and represent them as binary foreground masks with corresponding semantic labels. Currently, transform…