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20192023
most citedA Polynomial-time Solution for Robust Registration with Extreme Outlier Rates

11 citations · 19 across the 4 of their papers we have counts for

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6 papers · 1 filter

cs.CV20211 cited

Self-supervised Geometric Perception

Heng Yang, Wei Dong, Luca Carlone +1

We present self-supervised geometric perception (SGP), the first general framework to learn a feature descriptor for correspondence matching without any ground-truth geometric mode…

cs.CV2021

Dynamical Pose Estimation

Heng Yang, Chris Doran, Jean-Jacques Slotine

We study the problem of aligning two sets of 3D geometric primitives given known correspondences. Our first contribution is to show that this primitive alignment framework unifies…

cs.CV20204 cited

ROBIN: a Graph-Theoretic Approach to Reject Outliers in Robust Estimation using Invariants

Jingnan Shi, Heng Yang, Luca Carlone

Many estimation problems in robotics, computer vision, and learning require estimating unknown quantities in the face of outliers. Outliers are typically the result of incorrect da…

cs.CV20203 cited

A Dynamical Perspective on Point Cloud Registration

Heng Yang

We provide a dynamical perspective on the classical problem of 3D point cloud registration with correspondences. A point cloud is considered as a rigid body consisting of particles…

cs.CV2019

In Perfect Shape: Certifiably Optimal 3D Shape Reconstruction from 2D Landmarks

Heng Yang, Luca Carlone

We study the problem of 3D shape reconstruction from 2D landmarks extracted in a single image. We adopt the 3D deformable shape model and formulate the reconstruction as a joint op…

cs.CV2019

Graduated Non-Convexity for Robust Spatial Perception: From Non-Minimal Solvers to Global Outlier Rejection

Heng Yang, Pasquale Antonante, Vasileios Tzoumas +1

Semidefinite Programming (SDP) and Sums-of-Squares (SOS) relaxations have led to certifiably optimal non-minimal solvers for several robotics and computer vision problems. However,…