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Facial Expression Recognition

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Beyond Universality: The GCC-FER Dataset and Culture-Aware Adaptation for Dynamic Facial Expression Recognition

arXiv:2606.07063v1 Announce Type: cross Abstract: Dynamic Facial Expression Recognition (DFER) is a key enabling technology in affective computing, human-computer interaction, and intelligent multimedia systems. Despite the significant influence of cultural nuances on FER performance, most existing FER systems assume that emotional expressions are universally consistent across populations. This variation can be attributed to systematic differences in facial muscle activation patterns across...

arXiv CS 2d ago

Facial Expression Recognition in the Deep Learning Era: A Systematic Multi-Criteria Review of Methods, Models, Datasets, Performance, Challenges, and Future Research Directions

new Abstract: Facial Expression Recognition (FER) has advanced rapidly over the last decade, driven by the shift from handcrafted descriptors and shallow classifiers to deep convolutional, attention-based, vision-language, and foundation-model architectures, and by the parallel growth of large-scale in-the-wild benchmarks spanning categorical, dimensional, compound, micro-expression, Action Unit (AU), and intensity-estimation tasks. Yet the deep learning-based FER landscape has so far been...

arXiv CS 1d ago

A Multiscale Network with Supervised Contrastive Learning for Real-Time Facial Emotion Recognition

Announce Type: new Abstract: Real-time emotion recognition from facial expressions is a challenging task, particularly in video-based scenarios where multiple emotional states may occur over time. The difficulty increases further due to the fact that each emotional state is associated with facial expressions that vary significantly across individuals. The change of facial expressions portraying emotional state is not discrete, but rather continuous, which is very challenging to represent...

arXiv CS 8d ago

TokTalk: Expressive Real-time Facial Animation from Audio-LLM Tokens

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arXiv CS 9d ago

Phoneme-Level Visual Speech Recognition via Point-Visual Fusion and Language Model Reconstruction

Announce Type: replace Abstract: Visual Automatic Speech Recognition (V-ASR) is a challenging task that involves interpreting spoken language solely from visual information, such as lip movements and facial expressions. This task is notably challenging due to the absence of auditory cues and the visual ambiguity of phonemes that exhibit similar visemes-distinct sounds that appear identical in lip motions. Existing methods often aim to predict words or characters directly from visual cues,...

arXiv CS 8d ago

Iran allegedly used soccer clubs to spy on citizens, opposition group urges FIFA to ban team before World Cup

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Fox News 7h ago

ICE denies having a protester database. A letter to Congress sheds more light

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Age verification for social media, the beginning of the end for a free internet?

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Trump’s immigration enforcers look into buying ad data. Industry insiders fear what comes next.

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Politico EU 10d ago