Part-level Reconstruction for Self-Supervised Category-level 6D Object Pose Estimation with Coarse-to-Fine Correspondence Optimization

Zerui Zhang; Jun Yu; Liangxian Cui; Qiang Ling; Tianyu Liu

doi:10.1145/3664647.3681324

ScienceGate Book Chapters

JOURNAL ARTICLE

Part-level Reconstruction for Self-Supervised Category-level 6D Object Pose Estimation with Coarse-to-Fine Correspondence Optimization

Zerui Zhang Jun Yu Liangxian Cui Qiang Ling Tianyu Liu

Year: 2024 Pages: 9980-9988

DOI: 10.1145/3664647.3681324

Get Full-Text PDF Get Analytical Report

Keywords:

Pose Artificial intelligence Object (grammar) Computer vision Computer science 3D pose estimation Estimation Pattern recognition (psychology) Engineering

Metrics

Cited By

0.64

FWCI (Field Weighted Citation Impact)

Refs

0.63

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Robot Manipulation and Learning

Physical Sciences → Engineering → Control and Systems Engineering

Robotics and Sensor-Based Localization

Physical Sciences → Engineering → Aerospace Engineering

Image and Object Detection Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Part-level Reconstruction for Self-Supervised Category-level 6D Object Pose Estimation with Coarse-to-Fine Correspondence Optimization

Metrics

Citation History

Topics

Related Documents

Language-Assisted Reconstruction for Self-Supervised Category-level 6D Object Pose Estimation with Coarse-to-Fine Correspondence Optimization

OP-Align: Object-Level and Part-Level Alignment for Self-supervised Category-Level Articulated Object Pose Estimation

Rethinking Correspondence-based Category-Level Object Pose Estimation

Self-Supervised Category-Level 6D Object Pose Estimation With Optical Flow Consistency

Self-Supervised Category-Level 6D Object Pose Estimation with Deep Implicit Shape Representation