1 citations · 2 across the 10 of their papers we have counts for
10 papers
GeoWeaver: Accurate Long-Sequence 3D Reconstruction via Hierarchical Geometric Assembly
Tinghao Jiang, Sheng Tang, Shengzhe Wei +4
Long-sequence 3D reconstruction from RGB videos requires both accurate local geometry and globally consistent camera motion. Feed-forward models provide strong depth and pose predi…
UniQuery4R: Unified 4D Scene Reconstruction from a Single Query
Tiancheng Chen, Sheng Tang, Wenhua Jin +4
Reconstructing dynamic 4D scenes requires jointly estimating correspondence, geometry, object motion, and camera motion. Existing feed-forward methods typically predict dense task-…
GaussianGrow: Geometry-aware Gaussian Growing from 3D Point Clouds with Text Guidance
Weiqi Zhang, Junsheng Zhou, Haotian Geng +4
3D Gaussian Splatting has demonstrated superior performance in rendering efficiency and quality, yet the generation of 3D Gaussians still remains a challenge without proper geometr…
MoRe: Motion-aware Feed-forward 4D Reconstruction Transformer
Juntong Fang, Zequn Chen, Weiqi Zhang +4
Reconstructing dynamic 4D scenes remains challenging due to the presence of moving objects that corrupt camera pose estimation. Existing optimization methods alleviate this issue w…
MaterialRefGS: Reflective Gaussian Splatting with Multi-view Consistent Material Inference
Wenyuan Zhang, Jimin Tang, Weiqi Zhang +3
Modeling reflections from 2D images is essential for photorealistic rendering and novel view synthesis. Recent approaches enhance Gaussian primitives with reflection-related materi…
GAP: Gaussianize Any Point Clouds with Text Guidance
Weiqi Zhang, Junsheng Zhou, Haotian Geng +2
3D Gaussian Splatting (3DGS) has demonstrated its advantages in achieving fast and high-quality rendering. As point clouds serve as a widely-used and easily accessible form of 3D r…
Learning Bijective Surface Parameterization for Inferring Signed Distance Functions from Sparse Point Clouds with Grid Deformation
Takeshi Noda, Chao Chen, Junsheng Zhou +3
Inferring signed distance functions (SDFs) from sparse point clouds remains a challenge in surface reconstruction. The key lies in the lack of detailed geometric information in spa…
MultiPull: Detailing Signed Distance Functions by Pulling Multi-Level Queries at Multi-Step
Takeshi Noda, Chao Chen, Weiqi Zhang +3
Reconstructing a continuous surface from a raw 3D point cloud is a challenging task. Recent methods usually train neural networks to overfit on single point clouds to infer signed…
DiffGS: Functional Gaussian Splatting Diffusion
Junsheng Zhou, Weiqi Zhang, Yu-Shen Liu
3D Gaussian Splatting (3DGS) has shown convincing performance in rendering speed and fidelity, yet the generation of Gaussian Splatting remains a challenge due to its discreteness…
UDiFF: Generating Conditional Unsigned Distance Fields with Optimal Wavelet Diffusion
Junsheng Zhou, Weiqi Zhang, Baorui Ma +3
Diffusion models have shown remarkable results for image generation, editing and inpainting. Recent works explore diffusion models for 3D shape generation with neural implicit func…