2 citations · 2 across the 9 of their papers we have counts for
6 papers · 1 filter
CUPS: Improving Human Pose-Shape Estimators with Conformalized Deep Uncertainty
Harry Zhang, Luca Carlone
We introduce CUPS, a novel method for learning sequence-to-sequence 3D human shapes and poses from RGB videos with uncertainty quantification. To improve on top of prior work, we d…
CRISP: Object Pose and Shape Estimation with Test-Time Adaptation
Jingnan Shi, Rajat Talak, Harry Zhang +2
We consider the problem of estimating object pose and shape from an RGB-D image. Our first contribution is to introduce CRISP, a category-agnostic object pose and shape estimation…
CHAMP: Conformalized 3D Human Multi-Hypothesis Pose Estimators
Harry Zhang, Luca Carlone
We introduce CHAMP, a novel method for learning sequence-to-sequence, multi-hypothesis 3D human poses from 2D keypoints by leveraging a conditional distribution with a diffusion mo…
Theoretical Analysis for Expectation-Maximization-Based Multi-Model 3D Registration
David Jin, Harry Zhang, Kai Chang
We perform detailed theoretical analysis of an expectation-maximization-based algorithm recently proposed in for solving a variation of the 3D registration problem, named multi-mod…
GMKF: Generalized Moment Kalman Filter for Polynomial Systems with Arbitrary Noise
Sangli Teng, Harry Zhang, David Jin +3
This paper develops a new filtering approach for state estimation in polynomial systems corrupted by arbitrary noise, which commonly arise in robotics. We first consider a batch se…
Multi-Model 3D Registration: Finding Multiple Moving Objects in Cluttered Point Clouds
David Jin, Sushrut Karmalkar, Harry Zhang +1
We investigate a variation of the 3D registration problem, named multi-model 3D registration. In the multi-model registration problem, we are given two point clouds picturing a set…