Browse State-of-the-Art › Facial Expression Recognition
Facial Expression Recognition
164 papers with code · 7 benchmarks · 7 datasets archive 2025-07-28
Benchmarks archive 2025-07-28
7 leaderboard tables shown for this task, 7 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 |
|---|---|---|---|---|---|
| FER2013 (3 rows) | VGG | Facial Expression Recognition using Convolutional Neural Networks:... | code | — | Compare |
| Aff-Wild2 (1 row) | ARBEx | ARBEx: Attentive Feature Extraction with Reliability Balancing for... | code | — | Compare |
| AffectNet (1 row) | Up-Sampling | AffectNet: A Database for Facial Expression, Valence, and Arousal... | code | — | Compare |
| CMU-MOSEI (1 row) | ConCluGen | Multi-Task Multi-Modal Self-Supervised Learning for Facial... | code | — | Compare |
| FER+ (1 row) | ARBEx | ARBEx: Attentive Feature Extraction with Reliability Balancing for... | code | — | Compare |
| MELD (1 row) | ConCluGen | Multi-Task Multi-Modal Self-Supervised Learning for Facial... | code | — | Compare |
| RAF-DB (1 row) | ARBEx | ARBEx: Attentive Feature Extraction with Reliability Balancing for... | 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
7 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
2 subtasks in the archive's task tree.
Most implemented papers archive 2025-07-28
30 shown of 164 papers with code (532 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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1 Jul 2013 12 repositories listed Syntology ran 0 of 12 samples · 12 unverifiedThe ICML 2013 Workshop on Challenges in Representation Learning focused on three challenges: the black box learning challenge, the facial expression recognition challenge, and the multimodal learning challenge.
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3 Aug 2016 7 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)Crowd sourcing has become a widely adopted scheme to collect ground truth labels.
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23 Apr 2018 6 repositories listedWe then introduce the available datasets that are widely used in the literature and provide accepted data selection and evaluation principles for these datasets.
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23 Feb 2019 4 repositories listedDeep learning based facial expression recognition (FER) has received a lot of attention in the past few years.
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9 Dec 2016 4 repositories listedBased on the reported results alone, the performance impact of these factors is unclear.
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3 Dec 2021 3 repositories listedHowever, with the tremendous increase in images and videos with variations in face scale, appearance, expression, occlusion and pose, traditional face detectors are challenged to detect various "in the wild" faces.
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10 Jul 2021 3 repositories listedA dynamic transition mechanism is used to move from supervision loss in early learning to consistency loss for consensus of predictions among networks in the later stage.
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4 Feb 2019 3 repositories listedIn recent years, several works proposed an end-to-end framework for facial expression recognition, using deep learning models.
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7 Aug 2018 3 repositories listedThis paper presents a deep learning model to improve engagement recognition from images that overcomes the data sparsity challenge by pre-training on readily available basic facial expression data, before training on…
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19 Nov 2017 3 repositories listedOn the other hand, KD is proved to be useful for model compression for the FER problem, and we discovered that its effects gets more and more significant with the decreasing model size.
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17 Sep 2015 3 repositories listedThe proposed architecture achieves 99.
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11 Dec 2024 2 repositories listedWhile Multimodal Large Language Models (MLLMs) demonstrate robust general capabilities, they face considerable challenges in the field of affective computing, particularly in detecting subtle facial expressions and…
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23 Oct 2024 2 repositories listedIn addition, to further alleviate the scarcity of labeled and diverse images, we propose a Mixup-based data augmentation strategy tailored for facial images, and the loss weights of real and virtual images are…
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17 May 2024 2 repositories listedOur dataset of masked faces with mask region labels and source code will be available online.
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11 Mar 2024 2 repositories listedDue to the wide application area of point clouds and the recent advancements in deep neural networks, studies focusing on robust classification of the 3D point cloud data emerged.
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9 Mar 2024 2 repositories listedIn conclusion, this paper provides valuable insights into the potential applications and challenges of MLLMs in human-centric computing.
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9 Dec 2023 2 repositories listed Syntology ran 7 of 14 samples · 7 unverifiedAnd the TMAs capture and model the relationships of dynamic changes in facial expressions, effectively extending the pre-trained image model for videos.
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27 Mar 2023 2 repositories listedFor the data generation process, we consider generating facial expressions (FEs) by relying on two GANs.
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25 Sep 2022 2 repositories listed Syntology ran 1 of 5 samples · 4 unverifiedSpecifically, to find pairs of similar expressions from different identities, we define the inter-feature similarity as a transportation cost.
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31 Jul 2022 2 repositories listedTo reduce the reliance of deep neural solutions on labeled data, state-of-the-art semi-supervised methods have been proposed in the literature.
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4 Jul 2022 2 repositories listedIt is shown that the resulting facial features can be used for fast simultaneous prediction of students’ engagement levels (from disengaged to highly engaged), individual emotions (happy, sad, etc.,) and group-level…
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10 Jun 2022 2 repositories listedIn this paper, we consider the problem of real-time video-based facial emotion analytics, namely, facial expression recognition, prediction of valence and arousal and detection of action unit points.
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25 Mar 2022 2 repositories listedIn this paper, we consider the problem of real-time video-based facial emotion analytics, namely, facial expression recognition, prediction of valence and arousal and detection of action unit points.
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22 Jan 2022 2 repositories listedFacial expressions are a form of non-verbal communication that humans perform seamlessly for meaningful transfer of information.
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5 Jan 2022 2 repositories listedIn addition, the lack of high-quality paired data remains an obstacle for both methods.
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15 Sep 2021 2 repositories listedTo address these issues, we propose our DAN with three key components: Feature Clustering Network (FCN), Multi-head cross Attention Network (MAN), and Attention Fusion Network (AFN).
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29 Sep 2020 2 repositories listedFacial expression recognition(FER) in the wild is crucial for building reliable human-computer interactive systems.
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4 Aug 2020 2 repositories listedRecent deep models using graph convolutions provide an appropriate framework to handle such non-Euclidean data, but many of them, particularly those based on global graph Laplacians, lack expressiveness to capture local…
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8 Apr 2020 2 repositories listedOne of the most universal ways that people communicate is through facial expressions.
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24 Feb 2020 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)Annotating a qualitative large-scale facial expression dataset is extremely difficult due to the uncertainties caused by ambiguous facial expressions, low-quality facial images, and the subjectiveness of annotators.
Syntology lines on 5 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