6D Pose Estimation On Ycb Video 2

Métriques

ADDS AUC

Résultats

Résultats de performance de divers modèles sur ce benchmark

		Paper Title
ICG+	97.9	Fusing Visual Appearance and Geometry for Multi-modality 6DoF Object Tracking
FFB6D	96.6	FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimation
ICG	96.5	Iterative Corresponding Geometry: Fusing Region and Depth for Highly Efficient 3D Tracking of Textureless Objects
PVN3D	96.1	PVN3D: A Deep Point-wise 3D Keypoints Voting Network for 6DoF Pose Estimation
se3-TrackNet	95.71	se(3)-TrackNet: Data-driven 6D Pose Tracking by Calibrating Image Residuals in Synthetic Domains
CMCL6D	95.43	Enhancing 6-DoF Object Pose Estimation through Multiple Modality Fusion: A Hybrid CNN Architecture with Cross-Layer and Cross-Modal Integration
MaskedFusion	93.3	MaskedFusion: Mask-based 6D Object Pose Estimation
DenseFusion	93.1	DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion
PoseCNN+ICP	93.0	PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes

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