| Submission name | Synth train (default bboxs) | ||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Submission time (UTC) | May 29, 2026, 3:04 p.m. | ||||||||||||||
| User | GRAA | ||||||||||||||
| Task | Model-based 6D detection of seen objects | ||||||||||||||
| Dataset | XYZ-IBD | ||||||||||||||
| Description | - trained on given synthetic data - default bbox used | ||||||||||||||
| Evaluation scores |
|
| User | GRAA |
|---|---|
| Publication | |
| Implementation | |
| Training image modalities | RGB-D |
| Test image modalities | RGB-D |
| Description | NOCS coordinates were predicted from 2D image, and 3D–3D correspondences were established. Noisy points and inaccurate predictions were removed, and the Kabsch algorithm was used for 3D pose estimation. |
| Computer specifications | 1080 Ti |