Submission: FreeZe (SAM6D)/TUD-L
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| Submission name |
|
| Submission time (UTC) |
July 30, 2024, 12:41 p.m.
|
| User |
andreacaraffa
|
| Task |
Model-based 6D localization of unseen objects |
| Dataset |
TUD-L |
| Description |
|
| Evaluation scores |
| AR: | 0.949 |
| AR_MSPD: | 0.969 |
| AR_MSSD: | 0.969 |
| AR_VSD: | 0.909 |
| average_time_per_image: | 2.419 |
|
| User |
andreacaraffa
|
| Publication |
Caraffa et al: FreeZe: Training-free zero-shot 6D pose estimation with geometric and vision foundation models, ECCV 2024 |
| Implementation |
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| Training image modalities |
None |
| Test image modalities |
RGB-D |
| Description |
SAM6D masks are used.
|
| Computer specifications |
GPU A40; CPU Intel(R) Xeon(R) Silver 4316 @ 2.30GHz |