Submission name | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Submission time (UTC) | March 3, 2022, 2:15 p.m. | ||||||||||
User | yuecideng | ||||||||||
Task | 6D localization of seen objects | ||||||||||
Dataset | LM | ||||||||||
Training model type | Default | ||||||||||
Training image type | None | ||||||||||
Description | |||||||||||
Evaluation scores |
|
User | yuecideng |
---|---|
Publication | |
Implementation | https://github.com/yuecideng/Misc3D |
Training image modalities | D |
Test image modalities | D |
Description | A modified implementation of paper "Drost et al., Model globally, match locally: Efficient and robust 3D object recognition, CVPR 2010". Add sparse icp and dense icp for post processing. |
Computer specifications | intel@core i7-1165G7 2.8Gz 8 threads |