7 citations · 20 across the 10 of their papers we have counts for
12 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…
Track4World: Feedforward World-centric Dense 3D Tracking of All Pixels
Jiahao Lu, Jiayi Xu, Wenbo Hu +5
Estimating the 3D trajectory of every pixel from a monocular video is crucial and promising for a comprehensive understanding of the 3D dynamics of videos. Recent monocular 3D trac…
SkeletonGaussian: Editable 4D Generation through Gaussian Skeletonization
Lifan Wu, Ruijie Zhu, Yubo Ai +1
4D generation has made remarkable progress in synthesizing dynamic 3D objects from input text, images, or videos. However, existing methods often represent motion as an implicit de…
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…
ObjectGS: Object-aware Scene Reconstruction and Scene Understanding via Gaussian Splatting
Ruijie Zhu, Mulin Yu, Linning Xu +5
3D Gaussian Splatting is renowned for its high-fidelity reconstructions and real-time novel view synthesis, yet its lack of semantic understanding limits object-level perception. I…
DepthMaster: Taming Diffusion Models for Monocular Depth Estimation
Ziyang Song, Zerong Wang, Bo Li +5
Monocular depth estimation within the diffusion-denoising paradigm demonstrates impressive generalization ability but suffers from low inference speed. Recent methods adopt a singl…
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…
Plane2Depth: Hierarchical Adaptive Plane Guidance for Monocular Depth Estimation
Li Liu, Ruijie Zhu, Jiacheng Deng +3
Monocular depth estimation aims to infer a dense depth map from a single image, which is a fundamental and prevalent task in computer vision. Many previous works have shown impress…
ScaleDepth: Decomposing Metric Depth Estimation into Scale Prediction and Relative Depth Estimation
Ruijie Zhu, Chuxin Wang, Ziyang Song +3
Estimating depth from a single image is a challenging visual task. Compared to relative depth estimation, metric depth estimation attracts more attention due to its practical physi…
TIFace: Improving Facial Reconstruction through Tensorial Radiance Fields and Implicit Surfaces
Ruijie Zhu, Jiahao Chang, Ziyang Song +2
This report describes the solution that secured the first place in the "View Synthesis Challenge for Human Heads (VSCHH)" at the ICCV 2023 workshop. Given the sparse view images of…
EC-Depth: Exploring the consistency of self-supervised monocular depth estimation in challenging scenes
Ziyang Song, Ruijie Zhu, Chuxin Wang +3
Self-supervised monocular depth estimation holds significant importance in the fields of autonomous driving and robotics. However, existing methods are typically trained and tested…