| Submission name | |||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Submission time (UTC) | Sept. 26, 2023, 8:46 a.m. | ||||||||||||||||||||||||||
| User | zyMeteroid | ||||||||||||||||||||||||||
| Task | 2D detection of seen objects | ||||||||||||||||||||||||||
| Dataset | TUD-L | ||||||||||||||||||||||||||
| Description | |||||||||||||||||||||||||||
| Evaluation scores |
|
| User | zyMeteroid |
|---|---|
| Publication | Not yet |
| Implementation | Pytorch |
| Training image modalities | RGB |
| Test image modalities | RGB |
| Description | Submitted to: BOP Challenge 2023 Training data: only provided PBR Used 3D models: None Notes: Authors: Ruida Zhang, Ziqin Huang, Gu Wang, Xingyu Liu, Chenyangguang Zhang and Xiangyang Ji. (Tsinghua University) GDet2023 is based on YOLOv8, with stronger data augmentation and ranger optimizer. |
| Computer specifications | GPU RTX 3090; CPU AMD EPYC 7H12 64-Core Processor. |