activity
20182022
most citedSymmetryNet: Learning to Predict Reflectional and Rotational Symmetries of 3D Shapes from Single-View RGB-D Images

10 citations · 20 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV20221 cited

RayMVSNet: Learning Ray-based 1D Implicit Fields for Accurate Multi-View Stereo

Junhua Xi, Yifei Shi, Yijie Wang +2

Learning-based multi-view stereo (MVS) has by far centered around 3D convolution on cost volumes. Due to the high computation and memory consumption of 3D CNN, the resolution of ou…

cs.CV20226 cited

3DRM:Pair-wise relation module for 3D object detection

Yuqing Lan, Yao Duan, Yifei Shi +2

Context has proven to be one of the most important factors in object layout reasoning for 3D scene understanding. Existing deep contextual models either learn holistic features for…

cs.CV20212 cited

StablePose: Learning 6D Object Poses from Geometrically Stable Patches

Yifei Shi, Junwen Huang, Xin Xu +2

We introduce the concept of geometric stability to the problem of 6D object pose estimation and propose to learn pose inference based on geometrically stable patches extracted from…

cs.CV202010 cited

SymmetryNet: Learning to Predict Reflectional and Rotational Symmetries of 3D Shapes from Single-View RGB-D Images

Yifei Shi, Junwen Huang, Hongjia Zhang +3

We study the problem of symmetry detection of 3D shapes from single-view RGB-D images, where severely missing data renders geometric detection approach infeasible. We propose an en…

cs.CV2019

Rescan: Inductive Instance Segmentation for Indoor RGBD Scans

Maciej Halber, Yifei Shi, Kai Xu +1

In depth-sensing applications ranging from home robotics to AR/VR, it will be common to acquire 3D scans of interior spaces repeatedly at sparse time intervals (e.g., as part of re…

cs.CV20191 cited

Hierarchy Denoising Recursive Autoencoders for 3D Scene Layout Prediction

Yifei Shi, Angel Xuan Chang, Zhelun Wu +2

Indoor scenes exhibit rich hierarchical structure in 3D object layouts. Many tasks in 3D scene understanding can benefit from reasoning jointly about the hierarchical context of a…