SOURCE-LINKED INTELLIGENCE

Learned Parametric Emotion Editing: Real-Time Affective Filtering for On-Device Social Media Video

arXiv · AI, language, vision and robotics · article · Sep 18, 2026 · UTC

Problematic internet use affects a growing share of the population, yet common interventions, e.g., time limits, blocking, forced breaks, are coercive and easily circumvented. We explore a less restrictive alternative: adapting the emotional intensity of visual content. Prior work has shown that optimization can steer an image's affective content, but its per-image optimization cost makes it impractical for real-time deployment. We instead learn a model that predicts this transformation in a single forward pass: a MobileNetV4 backbone with FiLM-based emotion conditioning outputs parameters for

Read original source ↗ Open in workspace

recordType

paper

region

Global