
Welcome to the MuVi-Sync dataset! This collection provides a rich array of features for both music and video elements. Here's a breakdown of the directory structure: Music Features vevo_chord: Chord feature data vevo_note_density: Note density feature data vevo_loudness: Loudness feature data Video Features vevo_scene_offset: Scene offset feature data vevo_emotion: Emotion feature data 5c_l14p: 5 emotion categories (exciting, fearful, tense, sad, relaxing) 6c_l14p: 6 emotion categories (exciting, fearful, tense, sad, relaxing, neutral) vevo_semantic: Semantic feature vevo_motion: Motion feature Others vevo_meta: idlist.txt: List of features, titles, and YouTube IDs vevo: Original video files (.mp4) (on request by email: kjysmu@gmail.com) vevo_audio: Original audio files (.mp3) (on request by email: kjysmu@gmail.com) For detailed information about our dataset, please refer to our paper,"Video2Music: Suitable Music Generation from Videos using an Affective Multimodal Transformer model" [ Paper ] | [ GitHub ]
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
