Papers › Face Alignment using a 3D Deeply-initialized Ensemble of Regression Trees
Face Alignment using a 3D Deeply-initialized Ensemble of Regression Trees
Roberto Valle, José M. Buenaposada, Antonio Valdés, Luis Baumela
Face alignment algorithms locate a set of landmark points in images of faces taken in unrestricted situations. State-of-the-art approaches typically fail or lose accuracy in the presence of occlusions, strong deformations, large pose variations and ambiguous configurations. In this paper we present 3DDE, a robust and efficient face alignment algorithm based on a coarse-to-fine cascade of ensembles of regression trees. It is initialized by robustly fitting a 3D face model to the probability maps produced by a convolutional neural network. With this initialization we address self-occlusions and large face rotations. Further, the regressor implicitly imposes a prior face shape on the solution, addressing occlusions and ambiguous face configurations. Its coarse-to-fine structure tackles the combinatorial explosion of parts deformation. In the experiments performed, 3DDE improves the state-of-the-art in 300W, COFW, AFLW and WFLW data sets. Finally, we perform cross-dataset experiments that reveal the existence of a significant data set bias in these benchmarks.
Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Face Alignment | 300W | 3DDE | NME_inter-ocular (%, Challenge) | 4.92 | #15 of 48 | Archive leaderboard | report |
| Face Alignment | 300W | 3DDE | NME_inter-ocular (%, Common) | 2.69 | #15 of 48 | Archive leaderboard | report |
| Face Alignment | 300W | 3DDE | NME_inter-ocular (%, Full) | 3.13 | #15 of 48 | Archive leaderboard | report |
| Face Alignment | 300W | 3DDE | NME_inter-pupil (%, Challenge) | 7.10 | #15 of 48 | Archive leaderboard | report |
| Face Alignment | 300W | 3DDE | NME_inter-pupil (%, Common) | 3.73 | #15 of 48 | Archive leaderboard | report |
| Face Alignment | 300W | 3DDE | NME_inter-pupil (%, Full) | 4.39 | #15 of 48 | Archive leaderboard | report |
| Face Alignment | 300W Split 2 | 3DDE | AUC@8 (inter-ocular) | 53.94 | #5 of 7 | Archive leaderboard | report |
| Face Alignment | 300W Split 2 | 3DDE | FR@8 (inter-ocular) | 2.33 | #5 of 7 | Archive leaderboard | report |
| Face Alignment | 300W Split 2 | 3DDE | NME (inter-ocular) | 3.73 | #5 of 7 | Archive leaderboard | report |
| Face Alignment | COFW | 3DDE (Inter-pupil Norm) | NME (inter-pupil) | 5.11% | #24 of 28 | Archive leaderboard | report |
| Face Alignment | COFW | 3DDE (Inter-pupil Norm) | Recall at 80% precision (Landmarks Visibility) | 63.89 | #24 of 28 | Archive leaderboard | report |
| Face Alignment | WFLW | 3DDE | AUC@10 (inter-ocular) | 55.44 | #26 of 36 | Archive leaderboard | report |
| Face Alignment | WFLW | 3DDE | FR@10 (inter-ocular) | 5.04 | #26 of 36 | Archive leaderboard | report |
| Face Alignment | WFLW | 3DDE | NME (inter-ocular) | 4.68 | #26 of 36 | Archive leaderboard | report |
| Facial Landmark Detection | 300W | 3DDE (Inter-ocular Norm) | NME | 3.13 | #5 of 15 | Archive leaderboard | report |
| Facial Landmark Detection | AFLW-Full | 3DDE (Box height Norm, 19 landmarks - no earlobs) | Mean NME | 2.01 | #5 of 5 | 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.
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