6 papers
Sat3DGen: Comprehensive Street-Level 3D Scene Generation from Single Satellite Image
Ming Qian, Zimin Xia, Changkun Liu +6
Generating a street-level 3D scene from a single satellite image is a crucial yet challenging task. Current methods present a stark trade-off: geometry-colorization models achieve…
Mem3R: Streaming 3D Reconstruction with Hybrid Memory via Test-Time Training
Changkun Liu, Jiezhi Yang, Zeman Li +3
Streaming 3D perception is well suited to robotics and augmented reality, where long visual streams must be processed efficiently and consistently. Recent recurrent models offer a…
PLANA3R: Zero-shot Metric Planar 3D Reconstruction via Feed-Forward Planar Splatting
Changkun Liu, Bin Tan, Zeran Ke +6
This paper addresses metric 3D reconstruction of indoor scenes by exploiting their inherent geometric regularities with compact representations. Using planar 3D primitives - a well…
AIR-HLoc: Adaptive Retrieved Images Selection for Efficient Visual Localisation
Changkun Liu, Jianhao Jiao, Huajian Huang +3
State-of-the-art hierarchical localisation pipelines (HLoc) employ image retrieval (IR) to establish 2D-3D correspondences by selecting the top- most similar images from a refer…
GS-CPR: Efficient Camera Pose Refinement via 3D Gaussian Splatting
Changkun Liu, Shuai Chen, Yash Bhalgat +5
We leverage 3D Gaussian Splatting (3DGS) as a scene representation and propose a novel test-time camera pose refinement (CPR) framework, GS-CPR. This framework enhances the localiz…
LiteVLoc: Map-Lite Visual Localization for Image Goal Navigation
Jianhao Jiao, Jinhao He, Changkun Liu +4
This paper presents LiteVLoc, a hierarchical visual localization framework that uses a lightweight topo-metric map to represent the environment. The method consists of three sequen…