3 citations · 3 across the 4 of their papers we have counts for
4 papers
On the Importance of Accurate Geometry Data for Dense 3D Vision Tasks
HyunJun Jung, Patrick Ruhkamp, Guangyao Zhai +10
Learning-based methods to solve dense 3D vision problems typically train on 3D sensor data. The respectively used principle of measuring distances provides advantages and drawbacks…
PhoCaL: A Multi-Modal Dataset for Category-Level Object Pose Estimation with Photometrically Challenging Objects
Pengyuan Wang, HyunJun Jung, Yitong Li +6
Object pose estimation is crucial for robotic applications and augmented reality. Beyond instance level 6D object pose estimation methods, estimating category-level pose and shape…
Is my Depth Ground-Truth Good Enough? HAMMER -- Highly Accurate Multi-Modal Dataset for DEnse 3D Scene Regression
HyunJun Jung, Patrick Ruhkamp, Guangyao Zhai +9
Depth estimation is a core task in 3D computer vision. Recent methods investigate the task of monocular depth trained with various depth sensor modalities. Every sensor has its adv…
Polarimetric Pose Prediction
Daoyi Gao, Yitong Li, Patrick Ruhkamp +6
Light has many properties that vision sensors can passively measure. Colour-band separated wavelength and intensity are arguably the most commonly used for monocular 6D object pose…