Submission: SAM6D/TUD-L
Download submission
Submission name |
|
Submission time (UTC) |
Dec. 5, 2023, 7:22 a.m.
|
User |
jiehonglin
|
Task |
2D detection of unseen objects |
Dataset |
TUD-L |
Description |
|
Evaluation scores |
AP: | 0.537 |
AP50: | 0.850 |
AP75: | 0.617 |
AP_large: | 0.446 |
AP_medium: | 0.549 |
AP_small: | 0.575 |
AR1: | 0.634 |
AR10: | 0.655 |
AR100: | 0.659 |
AR_large: | 0.605 |
AR_medium: | 0.652 |
AR_small: | 0.700 |
average_time_per_image: | 2.393 |
|
User |
jiehonglin
|
Publication |
SAM-6D: Segment Anything Model Meets Zero-Shot 6D Object Pose Estimation |
Implementation |
https://github.com/JiehongLin/SAM-6D/ |
Training image modalities |
RGB-D |
Test image modalities |
RGB-D |
Description |
|
Computer specifications |
GeForce RTX 3090 24G; Inter (R) Xeon (R) CPU E5-2678 v3 @ 2.50Ghz |