Submission: FFB6D-PBR+Real/LM-O/submission1
Submission name |
submission1
|
Submission time (UTC) |
March 9, 2023, 5:52 a.m.
|
User |
CW_FLOYD
|
Task |
Pose estimation (BOP 2019-2022) |
Dataset |
LM-O |
Training model type |
Default |
Training image type |
Synthetic (only PBR images provided for BOP Challenge 2020 were used) |
Description |
We trained FFB6D model with PBR and real dataset.
|
Evaluation scores |
AR: | 0.677 |
AR_MSPD: | 0.776 |
AR_MSSD: | 0.723 |
AR_VSD: | 0.533 |
average_time_per_image: | 0.057 |
|
User |
CW_FLOYD
|
Publication |
ffb6d: a full flow bidirectional fusion network for 6d pose estimation, he et al., CVPR, 2021 |
Implementation |
|
Training image modalities |
RGB-D |
Test image modalities |
RGB-D |
Description |
|
Computer specifications |
NVIDIA RTX A4000 |