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20202022
most citedCPS++: Improving Class-level 6D Pose and Shape Estimation From Monocular Images With Self-Supervised Learning

35 citations · 38 across the 4 of their papers we have counts for

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Showing 2022Show all

2 papers · 1 filter

cs.CV2022★ 3 cited

HouseCat6D -- A Large-Scale Multi-Modal Category Level 6D Object Perception Dataset with Household Objects in Realistic Scenarios

HyunJun Jung, Guangyao Zhai, Shun-Cheng Wu +10

Estimating 6D object poses is a major challenge in 3D computer vision. Building on successful instance-level approaches, research is shifting towards category-level pose estimation…

cs.CV2022

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…