DenseFusion | Object Pose Estimation

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Object Pose Estimation · 2019 · CVPR · CCF A

DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion

Fuses RGB appearance with point cloud geometry and uses iterative refinement to improve RGB-D pose accuracy.

Paper Code

Research area

Object Pose Estimation

Task level

Instance-level

Object setting

Seen objects

Input modalities

RGB-Dpoint cloud

Requirements

camera intrinsicsdepthobject maskCAD model

Full paper metadata Authors, affiliations, research area, datasets, metrics, method tags, and reading status Expand

Authors: Chen Wang, Danfei Xu, Yuke Zhu, Roberto Martin-Martin, Cewu Lu, Li Fei-Fei, Silvio Savarese
Affiliations: Stanford University / Shanghai Jiao Tong University
Conference / journal: Conference · CVPR · CCF A
Research area: Object Pose Estimation
Code availability: Code available
Reading status: Overview:Available Deep Dive:Available
Task setting: Instance-level · Seen objects
Datasets: YCB-Video LINEMOD
Evaluation metrics: ADD ADD-S
Method tags: Dense Correspondences & Coordinate Fields Pose Refinement Instance-level Pose Estimation Absolute Pose Estimation
Requirements: camera intrinsicsdepthobject maskCAD model

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