Single Shot 6D | Object Pose Estimation

Object Pose Estimation · 2018 · CVPR · CCF A

Real-Time Seamless Single Shot 6D Object Pose Prediction

A YOLO-style single-stage network detects objects and regresses projected 3D bounding box corners, followed by PnP, targeting real-time multi-object inference.

Paper

Research area

Object Pose Estimation

Task level

Instance-level

Object setting

Seen objects

Input modalities

RGB

Requirements

camera intrinsicsCAD model3D bounding box keypoints

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

Authors: Bugra Tekin, Sudipta N. Sinha, Pascal Fua
Affiliations: EPFL / Microsoft
Conference / journal: Conference · CVPR · CCF A
Research area: Object Pose Estimation
Code availability: Unavailable / not yet recorded
Reading status: Overview:Pending Deep Dive:Pending
Task setting: Instance-level · Seen objects
Datasets: LINEMOD Occlusion LINEMOD
Evaluation metrics: ADD ADD-S 2D Projection
Method tags: Keypoints + PnP Multi-object Pose Estimation Instance-level Pose Estimation Absolute Pose Estimation
Requirements: camera intrinsicsCAD model3D bounding box keypoints

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