Emoception proposes the SALFT framework, selectively fine-tuning a video ViT to recognize changes in player arousal
The paper proposes SALFT (Selective Affective Layer Fine-Tuning), a framework that fine-tunes a Video Vision Transformer using a selection criterion based on layer-wise parameter L2 norm change to recognize changes in player arousal from gameplay footage.
Why it matters: The paper uses layer-wise parameter L2 norm change as its selection criterion and shows that updating only about 8% of parameters approaches full fine-tuning, useful for comparing compute costs against your own player emotion recognition pipeline.