A Controlled Study of CLIP-Based Body-Scene Fusion for Emotion Recognition in Context
Apparent emotion in natural images is often not visible from the face alone. The face may be small, hidden, or neutral, while posture and scene context carry much of the evidence. This work studies context-aware emotion recognition on EMOTIC with an image-only two-stream model. A ResNet-18 body stream encodes the target-person crop, and a CLIP ViT-B/16 scene stream encodes the full image. The fused feature predicts 26 categorical emotion labels and the continuous valence, arousal, and dominance values. This study examines whether small context-debiasing or rare-class training changes still help after adding a CLIP scene encoder. The clean two-stream model is compared with simplified CCIM-...
| Authors | Zubair Abbas, Muhammad Umair, Muqaddas Hameed |
|---|---|
| Primary category | cs.CV |
| Published | 20 June 2026 |
| Last updated at source | 23 June 2026 |
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