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To contribute to the need for emotional databases and affective tagging, the LIRIS-ACCEDE is proposed in this paper. LIRIS-ACCEDE is an Annotated Creative Commons Emotional DatabasE composed of 9800 video clips extracted from 160 movies shared under Creative Commons licenses. It allows to make this database publicly available without copyright issues. The 9800 video clips (each 8-12 seconds long) are sorted along the induced valence axis, from the video perceived the most negatively to the video perceived the most positively. The annotation was carried out by 1518 annotators from 89 different countries using crowd sourcing. A baseline late fusion scheme using ground truth from annotations is computed to predict emotion categories in video clips.
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Stored only when both papers are in the corpus — 52 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.