F2G-Pose
F2G-Pose predicts an object's 6D pose, metric size, and completed shape from aligned RGB, depth, camera intrinsics, and a binary target mask. The model does not require an object-specific CAD model or class label at inference.
Files and setup
f2g-pose.pt: selected inference checkpoint with its model configuration. SHA-256:bff06bd58a42fd805d8232f9ab7b4612b8eb833edf6b6cccd23e5040a8c9ca18.evaluation_results.json: complete SOPE/ROPE test metrics for the selected tensor-identical checkpoint.- NVIDIA RADIO v2.5-L source and checkpoint are separate downloads, required at runtime.
Follow the installation guide and usage guide. Save f2g-pose.pt in the source checkout's weights/ directory. The bundled ROPE example includes RGB, metric depth, mask, and intrinsics.
Results
| Dataset | AUC25 | AUC50 | AUC75 | Mean rotation | Mean translation |
|---|---|---|---|---|---|
| SOPE | 60.24 | 44.73 | 17.69 | 14.73° | 0.824 cm |
| ROPE | 46.75 | 28.19 | 6.17 | 26.99° | 1.181 cm |
These are complete test snapshot results. See the evaluation protocol for metric definitions and coverage. The current package changes only the embedded model name from the evaluated package; all 477 parameter tensors are identical.
Attribution
F2G-Pose integration code uses Apache-2.0. Third-party components and the Omni6DPose dataset retain their own terms. See THIRD_PARTY.md and the source repository.
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