Browse State-of-the-Art › 3D Facial Expression Recognition
3D Facial Expression Recognition
2 papers with code · 1 benchmark · 4 datasets archive 2025-07-28
3D facial expression recognition is the task of modelling facial expressions in 3D from an image or video.
( Image credit: Expression-Net )
Description from the archive 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 |
|---|---|---|---|---|---|
| 2017_test set (1 row) | aan | ExpNet: Landmark-Free, Deep, 3D Facial Expressions | 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
4 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
2 shown of 2 papers with code (13 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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23 Jan 2025 1 repository listedEmotion estimation in general is a field that has been studied for a long time, and several approaches exist using machine learning.
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2 Feb 2018 1 repository listedOur ExpNet CNN is applied directly to the intensities of a face image and regresses a 29D vector of 3D expression coefficients.
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