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6D Pose Estimation On Linemod

Métriques

Accuracy
Mean ADD
Mean IoU

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle
Accuracy
Mean ADD
Mean IoU
Paper TitleRepository
Single-shot Deep CNN90.37%55.9599.92Real-Time Seamless Single Shot 6D Object Pose Prediction-
HRNet+DSNT+BPnP99.21%--End-to-End Learnable Geometric Vision by Backpropagating PnP Optimization-
PVNet99%86.27-PVNet: Pixel-wise Voting Network for 6DoF Pose Estimation-
RePOSE-96.1-RePOSE: Fast 6D Object Pose Refinement via Deep Texture Rendering-
CullNet97.7%78.3-CullNet: Calibrated and Pose Aware Confidence Scores for Object Pose Estimation-
CDPN98.1%89.86-CDPN: Coordinates-Based Disentangled Pose Network for Real-Time RGB-Based 6-DoF Object Pose Estimation-
BB883.9%43.6-BB8: A Scalable, Accurate, Robust to Partial Occlusion Method for Predicting the 3D Poses of Challenging Objects without Using Depth-
E2E6DoF-86.8-End-to-End Differentiable 6DoF Object Pose Estimation with Local and Global Constraints-
EPro-PnP-6DoF v2-96.36-EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation-
EfficientPose-97.35-EfficientPose: An efficient, accurate and scalable end-to-end 6D multi object pose estimation approach-
HRNet (DSNT + BPnP)-93.3-End-to-End Learnable Geometric Vision by Backpropagating PnP Optimization-
Keypoint Detector Localization94.5%72.6-Estimating 6D Pose From Localizing Designated Surface Keypoints-
SSD-6D-76.399.4SSD-6D: Making RGB-based 3D detection and 6D pose estimation great again-
Pix2Pose-32-Pix2Pose: Pixel-Wise Coordinate Regression of Objects for 6D Pose Estimation-
RNNPose-97.37-RNNPose: Recurrent 6-DoF Object Pose Refinement with Robust Correspondence Field Estimation and Pose Optimization-
EPro-PnP-6DoF v1-95.8-EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation-
Augmented Autoencoder-28.7-Implicit 3D Orientation Learning for 6D Object Detection from RGB Images-
DPOD-95.2-DPOD: 6D Pose Object Detector and Refiner-
ROPE-95.61-Occlusion-Robust Object Pose Estimation with Holistic Representation-
YOLOv5-6D-96.84-YOLOv5-6D: Advancing 6-DoF Instrument Pose Estimation in Variable X-Ray Imaging Geometries
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