AffectNet
PulseAugur coverage of AffectNet — every cluster mentioning AffectNet across labs, papers, and developer communities, ranked by signal.
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Facial expression recognition models show significant bias, study finds
A new study published on arXiv examines bias in facial expression recognition (FER) datasets and models, finding that all four common datasets analyzed exhibit significant demographic bias, particularly concerning race.…
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New methods advance multi-task facial affect recognition with shared latent spaces and ensembling · 3 sources tracked
Researchers have developed novel approaches for multi-task facial affect recognition, tackling challenges like partially labeled datasets and imbalanced classes. One method utilizes a shared latent space to mediate diff…
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New LaCoVL-FER network improves facial expression recognition with landmark guidance
Researchers have developed LaCoVL-FER, a novel network designed for facial expression recognition (FER) in challenging real-world conditions. This system employs a landmark-guided adaptive encoder to refine visual featu…
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AI systems advance ambivalence and hesitancy recognition in video analysis · 8 sources tracked
Researchers have developed advanced methods for recognizing ambivalence and hesitancy in videos, participating in the 11th ABAW Challenge. One approach, the HSEmotion team's system, utilizes multi-task learning with fro…
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AI models encode Russell's emotion model, but rare classes pose geometric challenge
Two new arXiv papers explore the geometric properties of emotion representation in AI models. The first paper demonstrates that multimodal Transformers can perfectly align with Russell's circumplex model of affect, sugg…
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New network enhances facial expression recognition using landmarks and vision-language models
Researchers have developed a new network called LaCoVL-FER to improve facial expression recognition, particularly in challenging real-world conditions. This model integrates geometric information from facial landmarks w…