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MAFW

Introduced by Yuanyuan Liu et al. in MAFW: A Large-scale, Multi-modal, Compound Affective Database for Dynamic Facial Expression Recognition in the Wild1 Aug 2022 archive 2025-07-28

MAFW is a large-scale, multi-modal, compound affective database for dynamic facial expression recognition in the wild. It contains 10,045 video-audio clips, annotated with a compound emotional category and a couple of sentences that describe the subjects' affective behaviors in the clip. For the compound emotion annotation, each clip is categorized into one or more of the 11 widely-used emotions, i.e., anger, disgust, fear, happiness, neutral, sadness, surprise, contempt, anxiety, helplessness, and disappointment.

Benchmarks archive 2025-07-28

All 2 leaderboards whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

First row (archive order)PaperCode
Zero-Shot Facial Expression Recognition MAFW EmoCLIP UAR 25.86 EmoCLIP: A Vision-Language Method for Zero-Shot Video... nickyfot/emoclip 1 Compare
Emotion Recognition MAFW no rows — — 0 Compare

Papers archive 2025-07-28

1 shown of 1 paper with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 31. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

DateSamples run Syntology
EmoCLIP: A Vision-Language Method for Zero-Shot Video Facial Expression Recognition 1 1 25 Oct 2023 ran 4 of 10 samples (6 unverified)

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

MIT license

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • MAFW

1 variant name, as the archive lists them.

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