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Hanzhi Chang

8 accepted papers

2026

ExMesh: EXplicit Mesh Reconstruction with Topology Adaptation

CVPR 2026

Reconstructing surface meshes from multi-view images has remained a core challenge in recent years. Most existing methods, whether implicit or explicit, depend on intermediate representations and post-processing steps like Marching Cubes or TSDF fusion, often resulting in artifacts and fragmented ge

Cited by 0SourceScholar
2026

MeshSplat: Generalizable Sparse-View Surface Reconstruction via Gaussian Splatting

AAAI 2026technical

Surface reconstruction has been widely studied in computer vision and graphics. However, existing surface reconstruction works struggle to recover accurate scene geometry when the input views are extremely sparse. To address this issue, we propose MeshSplat, a generalizable sparse-view surface recon

Cited by 0SourcePDFScholar
2026

ReFlow: Self-correction Motion Learning for Dynamic Scene Reconstruction

CVPR 2026

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 suffer from incomplete scene initialization for dynamic regions, leading to unstable reconstruction and motion estimation,

Cited by 0SourceScholar
2025

Learning Neural Scene Representation from iToF Imaging

ICCV 2025poster

Indirect Time-of-Flight (iToF) cameras are popular for 3D perception because they are cost-effective and easy to deploy. They emit modulated infrared signals to illuminate the scene and process the received signals to generate amplitude and phase images. The depth is calculated from the phase using…

Cited by 0SourcePDFScholar
2025

Pamba: Enhancing Global Interaction in Point Clouds via State Space Model

AAAI 2025technical

Transformers have demonstrated impressive results for 3D point cloud semantic segmentation. However, the quadratic complexity of transformer makes computation costs high, limiting the number of points that can be processed simultaneously and impeding the modeling of long-range dependencies between o…

Cited by 0SourcePDFScholar
2025

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

ICCV 2025poster

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 dynamic 3D scenes. In this paper, we propose a simple yet effective approach, SAS, to integrate the open vocabulary capabil…

Cited by 0SourcePDFScholar
2024

MotionGS: Exploring Explicit Motion Guidance for Deformable 3D Gaussian Splatting

NeurIPS 2024poster

Dynamic scene reconstruction is a long-term challenge in the field of 3D vision. Recently, the emergence of 3D Gaussian Splatting has provided new insights into this problem. Although subsequent efforts rapidly extend static 3D Gaussian to dynamic scenes, they often lack explicit constraints on obje…