AI Pipeline Generates Animations from Text Prompts
A team of researchers has introduced Generative Animations, a system that transforms natural language instructions into animations ready for production by linking Large Language Models (LLMs) with the Segment Anything Model (SAM). This pipeline autonomously creates motion paths that consider scene geometry, manage depth-related occlusions, and respect 3D perspective transformations. Showcased through three examples—contour-following paths, orbital animations with z-order consideration, and motion aligned with perspective on altered objects—the system seeks to simplify the animation process, eliminating the need for manual preset choices or Bézier point plotting. This research is available on arXiv in the fields of computer vision and pattern recognition.
Key facts
- Generative Animations transforms natural language prompts into animations.
- The system chains LLMs for semantic parsing with SAM for visual grounding.
- Motion paths respect scene geometry, depth-based occlusions, and 3D perspective transforms.
- Three use cases: contour-following, orbital animations, perspective-aligned motion.
- Aims to eliminate manual preset selection and Bézier point plotting.
- Published on arXiv under Computer Vision and Pattern Recognition.
- Submission history and references available on arXiv.
- arXivLabs framework mentioned for experimental projects.
Entities
Institutions
- arXiv
- Semantic Scholar