Papers › On the power of data augmentation for head pose estimation
On the power of data augmentation for head pose estimation
Michael Welter
Deep learning has been impressively successful in the last decade in predicting human head poses from monocular images. However, for in-the-wild inputs the research community relies predominantly on a single training set, 300W-LP, of semisynthetic nature without many alternatives. This paper focuses on gradual extension and improvement of the data to explore the performance achievable with augmentation and synthesis strategies further. Modeling-wise a novel multitask head/loss design which includes uncertainty estimation is proposed. Overall, the thus obtained models are small, efficient, suitable for full 6 DoF pose estimation, and exhibit very competitive accuracy.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Face Alignment | AFLW2000-3D | OpNet | Balanced NME (2D Sparse Alignment) | 3.55% | #8 of 14 | Archive leaderboard | report |
| Head Pose Estimation | AFLW2000 | OpNet | Geodesic Error (GE) | 5.23 | #1 of 25 | Archive leaderboard | report |
| Head Pose Estimation | AFLW2000 | OpNet | MAE | 3.15 | #1 of 25 | Archive leaderboard | report |
| Head Pose Estimation | BIWI | OpNet | Geodesic Error (GE) | 7.01 | #8 of 29 | Archive leaderboard | report |
| Head Pose Estimation | BIWI | OpNet | Geodesic Error - aligned (GE) | 4.72 | #8 of 29 | Archive leaderboard | report |
| Head Pose Estimation | BIWI | OpNet | MAE (trained with other data) | 3.57 | #8 of 29 | Archive leaderboard | report |
| Head Pose Estimation | BIWI | OpNet | MAE-aligned (trained with other data) | 2.65 | #8 of 29 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections