2022

MaskGIT: Masked Generative Image Transformer

Chang, Huiwen, Zhang, Han, Jiang, Lu et al.

Understand

Generative transformers have experienced rapid popularity growth in the computer vision community in synthesizing high-fidelity and high-resolution images.

  • The best generative transformer models so far, however, still treat an image naively as a sequence of tokens, and decode an image sequentially following the raster scan ordering (i.e.
  • line-by-line).
  • We find this strategy neither optimal nor efficient.

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