Submission name | |||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Submission time (UTC) | Sept. 26, 2023, 8:48 a.m. | ||||||||||||||||||||||||||
User | zyMeteroid | ||||||||||||||||||||||||||
Task | Model-based 2D detection of seen objects | ||||||||||||||||||||||||||
Dataset | HB | ||||||||||||||||||||||||||
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. |