Method: GDRNPP-PBRReal-RGBD-MModel-Fast

User zyMeteroid
Publication not yet
Implementation Pytorch, code can be found at
Training image modalities RGB
Test image modalities RGB-D

GDRNPP for BOP2022 (Fast Version)

Authors: Xingyu Liu, Ruida Zhang, Chenyangguang Zhang, Bowen Fu, Jiwen Tang, Xiquan Liang, Jingyi Tang, Xiaotian Cheng, Yukang Zhang, Gu Wang, and Xiangyang Ji (Tsinghua University).

Based on GDRNPP_PBR_RGB_MModel, we utilize depth information to further refine the estimated pose. In order to fulfil the real-time application requirements, we implement a fast refinement module. We compare the rendered object depth and the observed depth to refine translation.

Computer specifications GPU RTX 3090; CPU AMD EPYC 7H12 64-Core Processor.

Public submissions

Date Submission name Dataset
2022-10-14 06:38 - T-LESS
2022-10-14 06:38 - TUD-L
2022-10-14 06:38 - LM-O
2022-10-14 06:39 - IC-BIN
2022-10-14 06:39 - HB
2022-10-14 06:39 - YCB-V
2022-10-14 07:27 - ITODD