| User | helose |
|---|---|
| Publication | RACE-6D: Real-time Accurate Coarse-to-finE object 6D Pose Transformer, CVPR 2026 Findings |
| Implementation | Pytorch, code can be found at https://github.com/Yoonwoo-Ha/RACE-6D |
| Views | Single |
| Test image modalities | RGB |
| Description | Training data: real + provided PBR Used 3D models: Default for other datasets Authors: Yoonwoo Ha, Hyungpil Moon (SungKyunKwan University). For LMO, TLESS, HB, ICBIN and ITODD, we only use the provided synthetic training data (PBR) in training. For YCBV and TUDL, we use the provided real data and synthetic data (PBR) in training. For detection, we developed a unified pose estimation model that encompasses the object detection process |
| Computer specifications | GPU RTX 3090; CPU intel i9-12900K |
| Date | Submission name | Dataset | ||
|---|---|---|---|---|
| 2026-04-14 20:19 | - | YCB-V | ||
| 2026-04-14 21:35 | - | TUD-L | ||
| 2026-04-28 05:59 | - | HB | ||
| 2026-04-28 06:11 | - | T-LESS | ||
| 2026-05-05 06:43 | - | IC-BIN | ||
| 2026-05-12 16:47 | - | ITODD | ||
| 2026-10-11 04:00 | - | LM-O |