Recomposed realities: animating still images via patch clustering and randomness
Journal:
arXiv
Published Date:
Jun 27, 2025
Abstract
We present a patch-based image reconstruction and animation method that uses
existing image data to bring still images to life through motion. Image patches
from curated datasets are grouped using k-means clustering and a new target
image is reconstructed by matching and randomly sampling from these clusters.
This approach emphasizes reinterpretation over replication, allowing the source
and target domains to differ conceptually while sharing local structures.
