MAX CAPACITY
Series

DEEP STYLE

published

Started
2021-04
Ended
2021-04
Status
published

Neural style transfer experiments applying AI-learned artistic transformations to VHS video source material. Four works exploring the aesthetic intersection of machine learning and analog video degradation.

DEEP STYLE

The DEEP STYLE series represents an intersection of artificial intelligence and analog video aesthetics. Using neural style transfer techniques, the work applies learned artistic transformations to source material derived from VHS video, creating hybrid aesthetic spaces where computational vision meets analog decay.

Concept and Process

Works in this series employ pre-trained neural style transfer models to apply artistic transformations to VHS-derived source imagery. This creates an unusual hybrid aesthetic—the digital intelligence of machine learning applied to the physical degradation patterns of magnetic tape. The resulting pieces occupy a liminal space between algorithmic and organic visual generation.

Works

Four pieces created on 2021-04-28:

  • DEEP STYLE + VHS + $TRSH (52743)
  • DEEP STYLE + VHS + $TRSH (52989)
  • DEEP STYLE + VHS + $TRSH (56003)
  • DEEP STYLE + VHS + MAX CAPACITY

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