Browse State-of-the-Art › 3D Face Alignment
3D Face Alignment
12 papers with code · 1 benchmark · 3 datasets archive 2025-07-28
Benchmarks archive 2025-07-28
1 leaderboard table shown for this task (1 more in the archive withheld as spam; see /not-shown), 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.
| Dataset | Best model (first row in archive order) | Paper | Code | Syntology | Compare |
|---|---|---|---|---|---|
| AFLW2000-3D (1 row) | Ours | Hierarchical binary CNNs for landmark localization with limited resources | code | — | Compare |
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
3 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
12 shown of 12 papers with code (26 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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21 Mar 2017 8 repositories listed Syntology ran 4 of 15 samples · 11 unverifiedTo this end, we make the following 5 contributions: (a) we construct, for the first time, a very strong baseline by combining a state-of-the-art architecture for landmark localization with a state-of-the-art residual…
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24 Aug 2017 5 repositories listedInstead, we compare our FPN with existing methods by evaluating how they affect face recognition accuracy on the IJB-A and IJB-B benchmarks: using the same recognition pipeline, but varying the face alignment method.
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19 Oct 2021 4 repositories listedOur synergy process leverages a representation cycle for 3DMM parameters and 3D landmarks.
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14 Dec 2020 2 repositories listedTests on AFLW2000-3D and BIWI show that our method runs at real-time and outperforms state of the art (SotA) face pose estimators.
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7 Dec 2020 2 repositories listedSome methods produce faces that cannot be realistically animated because they do not model how wrinkles vary with expression.
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12 Jun 2023 1 repository listedWe use raw MVS scans as supervision during training, but, once trained, TEMPEH directly predicts 3D heads in dense correspondence without requiring scans.
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6 Jun 2021 1 repository listed Syntology ran 0 of 8 samples · 8 unverifiedThree-dimensional face dense alignment and reconstruction in the wild is a challenging problem as partial facial information is commonly missing in occluded and large pose face images.
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30 Aug 2019 1 repository listed3D face alignment of monocular images is a crucial process in the recognition of faces with disguise.
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19 Apr 2019 1 repository listedThen, an end-to-end pipeline is designed to jointly regress the proposed volumetric representation and the coordinate vector.
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14 Aug 2018 1 repository listedTo this end, we make the following contributions: (a) we are the first to study the effect of neural network binarization on localization tasks, namely human pose estimation and face alignment.
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20 Feb 2018 1 repository listedWe present a method that can evaluate a RANSAC hypothesis in constant time, i.
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29 Sep 2016 1 repository listedThis paper describes our submission to the 1st 3D Face Alignment in the Wild (3DFAW) Challenge.
Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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