| User | r10922190 |
|---|---|
| Publication | Hong, Zong-Wei and Hung, Yen-Yang and Chen, Chu-Song: RDPN6D: Residual-based Dense Point-wise Network for 6Dof Object Pose Estimation Based on RGB-D Images, CVPRW 2024 |
| Implementation | https://github.com/AI-Application-and-Integration-Lab/RDPN6D |
| Implementation | https://github.com/AI-Application-and-Integration-Lab/RDPN6D |
| Views | single |
| Test image modalities | RGB-D |
| Description | Submitted to: BOP Challenge 2024 Training data: real + provided PBR Used 3D models: Reconstructed for T-LESS, default for other datasets Notes: Authors: Hong, Zong-Wei and Hung, Yen-Yang and Chen, Chu-Song (National Taiwan University) Following GDRNPP, the detector is using YOLOX trained on real + PBR datasets and we also utilize depth information (CIR) to further refine the estimated pose. A network is trained for each object. |
| Computer specifications | RTX3090 |
| Date | Submission name | Dataset | ||
|---|---|---|---|---|
| 2024-01-28 14:08 | cir | TUD-L | ||
| 2024-01-28 18:26 | cir | IC-BIN | ||
| 2024-01-28 18:46 | cir | HB | ||
| 2024-01-29 17:21 | cir | YCB-V | ||
| 2024-01-29 17:44 | cir | T-LESS | ||
| 2024-01-30 02:43 | cir | ITODD | ||
| 2024-01-30 03:15 | cir | LM-O |