REVIEW 5 cited by
Generative Disco: Text-to-Video Generation for Music Visualization
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
Signed reviews
read the original abstract
Visuals can enhance our experience of music, owing to the way they can amplify the emotions and messages conveyed within it. However, creating music visualization is a complex, time-consuming, and resource-intensive process. We introduce Generative Disco, a generative AI system that helps generate music visualizations with large language models and text-to-video generation. The system helps users visualize music in intervals by finding prompts to describe the images that intervals start and end on and interpolating between them to the beat of the music. We introduce design patterns for improving these generated videos: transitions, which express shifts in color, time, subject, or style, and holds, which help focus the video on subjects. A study with professionals showed that transitions and holds were a highly expressive framework that enabled them to build coherent visual narratives. We conclude on the generalizability of these patterns and the potential of generated video for creative professionals.
Forward citations
Cited by 5 Pith papers
-
Not Like Us, Hunty: Measuring Perceptions and Behavioral Effects of Minoritized Anthropomorphic Cues in LLMs
An experiment with 985 participants found that LLM agents using AAE or Queer slang did not increase reliance or trust over a standard English agent, and AAE speakers significantly preferred the standard English agent.
-
VideoDiff: Human-AI Video Co-Creation with Alternatives
Aligned timeline and transcript views for multiple AI-generated video edits let creators compare and refine alternatives roughly twice as fast, with lower workload and higher final-video satisfaction, in a within-subj...
-
LeviTor: 3D Trajectory Oriented Image-to-Video Synthesis
LeviTor controls 3D object trajectories in generated videos by feeding K-means clustered mask points with estimated depth into a video diffusion model.
-
Examining the Usage of Generative AI Models in Student Learning Activities for Software Programming
ChatGPT helps students pass programming tests but not understand concepts; both heavy reliance and minimal use lead to weaker learning.
-
Inkspire: Supporting Design Exploration with Generative AI through Analogical Sketching
A sketch-driven text-to-image interface with analogical inspiration and sketch scaffolding increases designers' self-reported inspiration, exploration, and co-creation compared to a ControlNet baseline.
Discussion (0). Continue with ORCID to comment.