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LineMOD Benchmark (6D Pose Estimation using RGB)
6D Pose Estimation using RGB refers to the task of determining the six degree-of-freedom (6D) pose of an object in 3D space based on RGB images. This involves estimating the position and orientation of an object in a scene, and is a fundamental problem in computer vision and robotics. In this task, the goal is to estimate the 6D pose of an object given an RGB image of the object and the scene, which can be used for tasks such as robotic manipulation, augmented reality, and scene reconstruction.
The archive carries no text for this table; the description above is the archive's text for the task 6D Pose Estimation using RGB. archive 2025-07-28
Over time archive 2025-07-28
The chart needs JavaScript; the table below carries every value.
Direction inferred from the metric name, not from the archive: Accuracy (ADD) (higher is better), Accuracy (higher is better), Mean IoU (higher is better). Not inferred (points only, no best-so-far line): Mean ADD. Points are placed at the row's paper date; 22 of 22 rows carry one.
Results archive 2025-07-28
Archive rows end at the archive snapshot, 2025-07-28: no result published after that date is in this table. Rank is the archive's row order at that snapshot; not re-ranked here. Metric values are the archive's strings. Column headers sort the table in your browser; each row keeps its archive rank.
| Paper | Code | Ran Syntology | Report | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | RNNPose | 97.37 | 97.37% | – | Paper | Code | 2022 | 0 of 5 ran · 5 unverified | report | ||
| 2 | EfficientPose | 97.35 | 97.35% | – | Paper | Code | 2020 | linked, not harvested | report | ||
| 3 | YOLOv5-6D | 96.84 | 96.84% | – | Paper | Code | 2024 | linked, not harvested | report | ||
| 4 | EPro-PnP-6DoF v2 | 96.36 | – | Paper | Code | 2023 | 1 of 8 ran · 7 unverified | report | |||
| 5 | RePOSE | 96.1 | 96.1% | – | Paper | Code | 2021 | 0 of 10 ran · 10 unverified | report | ||
| 6 | EPro-PnP-6DoF v1 | 95.8 | – | Paper | Code | 2022 | linked, not harvested | report | |||
| 7 | ROPE | 95.61 | 95.61% | – | Paper | Code | 2021 | linked, not harvested | report | ||
| 8 | DPOD | 95.2 | 95.15% | – | Paper | Code | 2019 | 1 of 8 ran · 7 unverified | report | ||
| 9 | HRNet (DSNT + BPnP) | 93.3 | – | Paper | Code | 2019 | 0 of 2 ran · 2 unverified | report | |||
| 10 | HybridPose | 91.3 | 94.5% | – | Paper | Code | 2020 | 5 of 5 ran · 0 unverified | report | ||
| 11 | CDPN | 89.86 | 89.86% | 98.1% | – | Paper | – | 2019 | no code linked | report | |
| 12 | PoseCNN + DeepIM | 88.6 | 88.1% | 97.5 | – | Paper | Code | 2018 | 0 of 2 ran · 2 unverified | report | |
| 13 | E2E6DoF | 86.8 | – | Paper | – | 2020 | no code linked | report | |||
| 14 | PVNet | 86.27 | 86.27% | 99% | – | Paper | Code | 2018 | 2 of 11 ran · 9 unverified | report | |
| 15 | CullNet | 78.3 | 78.3% | 97.7% | – | Paper | Code | 2019 | linked, not harvested | report | |
| 16 | SSD-6D | 76.3 | 99.4 | – | Paper | Code | 2017 | linked, not harvested | report | ||
| 17 | Keypoint Detector Localization | 72.6 | 94.5% | – | Paper | Code | 2018 | 0 of 7 ran · 7 unverified | report | ||
| 18 | Single-shot Deep CNN | 55.95 | 90.37% | 99.92 | – | Paper | Code | 2017 | linked, not harvested | report | |
| 19 | BB8 | 43.6 | 43.6% | 83.9% | – | Paper | Code | 2017 | linked, not harvested | report | |
| 20 | Pix2Pose | 32 | – | Paper | Code | 2019 | 0 of 8 ran · 8 unverified | report | |||
| 21 | Augmented Autoencoder | 28.7 | – | Paper | Code | 2019 | 0 of 5 ran · 5 unverified | report | |||
| 22 | HRNet+DSNT+BPnP | 93.27% | 99.21% | – | Paper | Code | 2019 | 0 of 2 ran · 2 unverified | report |
All 22 rows shown. 22 link to a paper page on this site; 0 are marked as using additional training data in the archive. No GitHub stars are tracked; "Code" is the first repository the archive lists for the row. The archive carries no row tags, review links or community-submitted rows for this table; none are shown. archive 2025-07-28
Syntology Ran reads "N of M ran · U unverified": of the M code samples Syntology harvested from repositories linked to that row's paper (joined by arXiv id), N executed on a synthesized input and the other U = M−N are unverified (harvested, no recorded run). It counts code from repositories linked to that row's paper, not this result: the row's number was not reproduced and nothing here is a correctness claim. The other cell texts mean no graph line for the row: "linked, not harvested" (the archive links code, Syntology has not harvested it), "no code linked" (no code link in the archive), "not matched" (the row's paper URL matched no paper on this site). 12 rows have a graph line, from 11 distinct papers; 4 rows (4 papers) have at least one sample that ran. Counting each paper once: Syntology ran 9 of 71 samples; 62 unverified. Separately, 9 of those 71 are pointer-only (licence): the site points at that code rather than redistributing it, a licence property recorded for ran and unverified samples alike; each cell's tooltip carries the row's own pointer-only count. Read from the graph 2026-09-24. Per-sample status is on the paper page.
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