Submission: SAM6D/TUD-L
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Submission name |
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Submission time (UTC) |
Dec. 5, 2023, 7:46 a.m.
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User |
jiehonglin
|
Task |
2D segmentation of unseen objects |
Dataset |
TUD-L |
Description |
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Evaluation scores |
AP: | 0.569 |
AP50: | 0.885 |
AP75: | 0.674 |
AP_large: | 0.526 |
AP_medium: | 0.567 |
AP_small: | 0.647 |
AR1: | 0.629 |
AR10: | 0.649 |
AR100: | 0.650 |
AR_large: | 0.612 |
AR_medium: | 0.640 |
AR_small: | 0.750 |
average_time_per_image: | 2.393 |
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User |
jiehonglin
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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 |
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Computer specifications |
GeForce RTX 3090 24G; Inter (R) Xeon (R) CPU E5-2678 v3 @ 2.50Ghz |