| User | epi |
|---|---|
| Publication | |
| Implementation | |
| Views | single |
| Test image modalities | RGB |
| Description | The presented results were achieved by FoundPose with the featuremetric refinement (row 6 of Table 1 in [A]). In this submission, FoundPose uses default CNOS-FastSAM [B] segmentations provided for BOP'23. For pose estimation, the method uses features from layer 18 of DINOv2 (ViT-L) with registers [C]. Note that FoundPose doesn't do any task-specific training -- it only uses frozen FastSAM (via CNOS) and frozen DINOv2. [A] Anonymous: FoundPose: Unseen Object Pose Estimation with Foundation Features. [B] Nguyen et al.: CNOS: A Strong Baseline for CAD-based Novel Object Segmentation, ICCVW 2023. [C] Darcet et al.: Vision transformers need registers, arXiv 2023. |
| Computer specifications | Tesla P100 16GB |
| Date | Submission name | Dataset | ||
|---|---|---|---|---|
| 2023-11-15 18:05 | FoundPose+FeatRef | ITODD | ||
| 2023-11-15 18:14 | FoundPose+FeatRef | HB | ||
| 2024-01-27 11:32 | FoundPose+FeatRef | IC-BIN | ||
| 2024-01-29 10:49 | FoundPose+FeatRef | YCB-V | ||
| 2024-01-29 10:49 | FoundPose+FeatRef | T-LESS | ||
| 2024-01-29 10:50 | FoundPose+FeatRef | TUD-L | ||
| 2024-01-29 10:51 | FoundPose+FeatRef | LM-O |