| Submission name | |||||||||||
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| Submission time (UTC) | Sept. 26, 2024, 2:41 a.m. | ||||||||||
| User | jysir | ||||||||||
| Task | Model-based 6D localization of seen objects | ||||||||||
| Dataset | LM-O | ||||||||||
| Description | |||||||||||
| Evaluation scores |
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| User | jysir |
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| Publication | |
| Implementation | |
| Training image modalities | RGB-D |
| Test image modalities | RGB-D |
| Description | We trained our model using PBR data, employing YOLOX for object detection and segmentation, and used default 3D models without ICP refinement. The architecture consisted of a single model for all objects within each dataset, combining object detection and pose regression. Author: Jingyang Liu. |
| Computer specifications | RTX3090 |