| Submission name | |||||||||||||||||||||||||||
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| Submission time (UTC) | Sept. 25, 2023, 3:30 p.m. | ||||||||||||||||||||||||||
| User | zyMeteroid | ||||||||||||||||||||||||||
| Task | Model-based 2D detection of seen objects | ||||||||||||||||||||||||||
| Dataset | TUD-L | ||||||||||||||||||||||||||
| Description | |||||||||||||||||||||||||||
| Evaluation scores |
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| User | zyMeteroid |
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| Publication | Not yet |
| Implementation | Pytorch |
| Training image modalities | RGB |
| Test image modalities | RGB |
| Description | Submitted to: BOP Challenge 2023 Training data: real + 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. |