Papers › EmoCLIP: A Vision-Language Method for Zero-Shot Video Facial Expression Recognition

EmoCLIP: A Vision-Language Method for Zero-Shot Video Facial Expression Recognition

25 Oct 2023arXiv:2310.16640archive 2025-07-28

Niki Maria Foteinopoulou, Ioannis Patras

Facial Expression Recognition (FER) is a crucial task in affective computing, but its conventional focus on the seven basic emotions limits its applicability to the complex and expanding emotional spectrum. To address the issue of new and unseen emotions present in dynamic in-the-wild FER, we propose a novel vision-language model that utilises sample-level text descriptions (i.e. captions of the context, expressions or emotional cues) as natural language supervision, aiming to enhance the learning of rich latent representations, for zero-shot classification. To test this, we evaluate using zero-shot classification of the model trained on sample-level descriptions on four popular dynamic FER datasets. Our findings show that this approach yields significant improvements when compared to baseline methods. Specifically, for zero-shot video FER, we outperform CLIP by over 10\% in terms of Weighted Average Recall and 5\% in terms of Unweighted Average Recall on several datasets. Furthermore, we evaluate the representations obtained from the network trained using sample-level descriptions on the downstream task of mental health symptom estimation, achieving performance comparable or superior to state-of-the-art methods and strong agreement with human experts. Namely, we achieve a Pearson's Correlation Coefficient of up to 0.85 on schizophrenia symptom severity estimation, which is comparable to human experts' agreement. The code is publicly available at: https://github.com/NickyFot/EmoCLIP.

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CCC nickyfot/emoclip/utils.py official repository ran fingerprinted Apache-2.0 (permissive) · 1bf0d337eeb02b7c · report
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load_video nickyfot/emoclip/DataLoaders/utils.py official repository unverified Apache-2.0 (permissive) · b7d567db51876aea · report

Tasks

Facial Expression RecognitionFacial Expression Recognition (FER)Language ModellingZero-Shot Facial Expression RecognitionZero-Shot Learning

1 archive task tag without a task page not shown.

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Zero-Shot Facial Expression Recognition MAFW EmoCLIP UAR 25.86 #1 of 1 Archive leaderboard report
Zero-Shot Facial Expression Recognition MAFW EmoCLIP WAR 33.49 #1 of 1 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

CLIPFocus

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