Two in One Go: Single-stage Emotion Recognition with Decoupled Subject-context Transformer

Understand

Emotion recognition aims to discern the emotional state of subjects within an image, relying on subject-centric and contextual visual cues.

• Current approaches typically follow a two-stage pipeline: first localize subjects by off-the-shelf detectors, then perform emotion classification through the late fusion of subject and context features.
• However, the complicated paradigm suffers from disjoint training stages and limited interaction between fine-grained subject-context elements.
• To address the challenge, we present a single-stage emotion recognition approach, employing a Decoupled Subject-Context Transformer (DSCT), for simultaneous subject localization and emotion classification.