4 citations · 4 across the 6 of their papers we have counts for
4 papers · 1 filter
Pseudo-keypoint RKHS Learning for Self-supervised 6DoF Pose Estimation
Yangzheng Wu, Michael Greenspan
We address the simulation-to-real domain gap in six degree-of-freedom pose estimation (6DoF PE), and propose a novel self-supervised keypoint voting-based 6DoF PE framework, effect…
Learning Better Keypoints for Multi-Object 6DoF Pose Estimation
Yangzheng Wu, Michael Greenspan
We address the problem of keypoint selection, and find that the performance of 6DoF pose estimation methods can be improved when pre-defined keypoint locations are learned, rather…
Keypoint Cascade Voting for Point Cloud Based 6DoF Pose Estimation
Yangzheng Wu, Alireza Javaheri, Mohsen Zand +1
We propose a novel keypoint voting 6DoF object pose estimation method, which takes pure unordered point cloud geometry as input without RGB information. The proposed cascaded keypo…
Vote from the Center: 6 DoF Pose Estimation in RGB-D Images by Radial Keypoint Voting
Yangzheng Wu, Mohsen Zand, Ali Etemad +1
We propose a novel keypoint voting scheme based on intersecting spheres, that is more accurate than existing schemes and allows for fewer, more disperse keypoints. The scheme is ba…