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6D Pose Estimation Using Rgbd On Real275

Metrics

mAP 10, 2cm
mAP 10, 5cm
mAP 3DIou@50
mAP 3DIou@75
mAP 5, 2cm
mAP 5, 5cm

Results

Performance results of various models on this benchmark

Model Name
mAP 10, 2cm
mAP 10, 5cm
mAP 3DIou@50
mAP 3DIou@75
mAP 5, 2cm
mAP 5, 5cm
Paper TitleRepository
UDA-COPE56.966.082.662.530.434.8UDA-COPE: Unsupervised Domain Adaptation for Category-level Object Pose Estimation-
CenterSnap-64.380.2--29.1CenterSnap: Single-Shot Multi-Object 3D Shape Reconstruction and Categorical 6D Pose and Size Estimation
BundleTrack-----87.4BundleTrack: 6D Pose Tracking for Novel Objects without Instance or Category-Level 3D Models
FS-Net-60.892.263.5-28.2FS-Net: Fast Shape-based Network for Category-Level 6D Object Pose Estimation with Decoupled Rotation Mechanism
gcasp64.276.379.065.346.954.7Generative Category-Level Shape and Pose Estimation with Semantic Primitives
DualPoseNet5066.879.8--35.9DualPoseNet: Category-level 6D Object Pose and Size Estimation Using Dual Pose Network with Refined Learning of Pose Consistency
GPV-Pose-73.38364.43242.9GPV-Pose: Category-level Object Pose Estimation via Geometry-guided Point-wise Voting
GenPose https://github.com/Jiyao06/GenPose72.484.0--52.160.9GenPose: Generative Category-level Object Pose Estimation via Diffusion Models-
CPPF-44.926.4--16.9CPPF: Towards Robust Category-Level 9D Pose Estimation in the Wild
NOCS (128 bins)-26.780.5--9.5Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation
6-PACK-----33.36-PACK: Category-level 6D Pose Tracker with Anchor-Based Keypoints
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