6 papers
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…
MeshSplat: Generalizable Sparse-View Surface Reconstruction via Gaussian Splatting
Hanzhi Chang, Ruijie Zhu, Wenjie Chang +5
Surface reconstruction has been widely studied in computer vision and graphics. However, existing surface reconstruction works struggle to recover accurate scene geometry when the…
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…
Pamba: Enhancing Global Interaction in Point Clouds via State Space Model
Zhuoyuan Li, Yubo Ai, Jiahao Lu +7
Transformers have demonstrated impressive results for 3D point cloud semantic segmentation. However, the quadratic complexity of transformer makes computation costs high, limiting…
DN-4DGS: Denoised Deformable Network with Temporal-Spatial Aggregation for Dynamic Scene Rendering
Jiahao Lu, Jiacheng Deng, Ruijie Zhu +4
Dynamic scenes rendering is an intriguing yet challenging problem. Although current methods based on NeRF have achieved satisfactory performance, they still can not reach real-time…
MotionGS: Exploring Explicit Motion Guidance for Deformable 3D Gaussian Splatting
Ruijie Zhu, Yanzhe Liang, Hanzhi Chang +5
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. Altho…