MatchU: Matching Unseen Objects for 6D Pose Estimation from RGB-D Images

no code implementations • 3 Mar 2024 • Junwen Huang, Hao Yu, Kuan-Ting Yu, Nassir Navab, Slobodan Ilic, Benjamin Busam

MatchU is a generic approach that fuses 2D texture and 3D geometric cues for 6D pose prediction of unseen objects.

6D Pose Estimation Pose Prediction

SSR-2D: Semantic 3D Scene Reconstruction from 2D Images

no code implementations • 7 Feb 2023 • Junwen Huang, Alexey Artemov, Yujin Chen, Shuaifeng Zhi, Kai Xu, Matthias Nießner

In this work, we explore a central 3D scene modeling task, namely, semantic scene reconstruction without using any 3D annotations.

3D Scene Reconstruction Colorization +1

StablePose: Learning 6D Object Poses from Geometrically Stable Patches

no code implementations • CVPR 2021 • Yifei Shi, Junwen Huang, Xin Xu, Yifan Zhang, Kai Xu

According to the theory of geometric stability analysis, a minimal set of three planar/cylindrical patches are geometrically stable and determine the full 6DoFs of the object pose.

6D Pose Estimation using RGB Object +1

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

no code implementations • 2 Aug 2020 • Yifei Shi, Junwen Huang, Hongjia Zhang, Xin Xu, Szymon Rusinkiewicz, Kai Xu

We propose an end-to-end deep neural network which is able to predict both reflectional and rotational symmetries of 3D objects present in the input RGB-D image.

Multi-Task Learning Symmetry Detection