title: Wavelets Are All You Need for Autoregressive Image Generation
summary: In this paper, we take a new approach to autoregressive image generation that
  is based on two main ingredients. The first is wavelet image coding, which
  allows to tokenize the visual details of an image from coarse to fine details
  by ordering the information starting with the most significant bits of the most
  significant wavelet coefficients. The second is a variant of a language
  transformer whose architecture is re-designed and optimized for token sequences
  in this 'wavelet language'. The transformer learns the significant statistical
  correlations within a token sequence, which are the manifestations of
  well-known correlations between the wavelet subbands at various resolutions. We
  show experimental results with conditioning on the generation process.
paper_authors._id: 6682e225f80f97532edd4a00
paper_authors.name: Wael Mattar
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-07-03T15:05:51.162Z
paper_authors._id: 65faee3e9e96d231ddcf5183
paper_authors.avatarUrl: /avatars/6530a3c79655509fdde83ff7c694603e.svg
paper_authors.fullname: Wael Mattar
paper_authors.type: user
paper_authors.user: WaelMattar
paper_authors._id: 6682e225f80f97532edd4a01
paper_authors.name: Idan Levy
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2024-07-02T07:39:14.384Z
paper_authors._id: 64257699120a3ed323326b8c
paper_authors.avatarUrl: /avatars/2b8ee4feb99700791a7aa045506518ef.svg
paper_authors.fullname: Idan Levy
paper_authors.type: user
paper_authors.user: idanlevy
paper_authors._id: 6682e225f80f97532edd4a02
paper_authors.name: Nir Sharon
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-07-03T15:05:37.290Z
paper_authors._id: 65732a9714bfb7d56f80d352
paper_authors.avatarUrl: /avatars/b89073e4cd8e1e6ee458399e13936b05.svg
paper_authors.fullname: King
paper_authors.type: user
paper_authors.user: NirSharon
paper_authors._id: 6682e225f80f97532edd4a03
paper_authors.name: Shai Dekel
paper_title: Wavelets Are All You Need for Autoregressive Image Generation
paper_summary: In this paper, we take a new approach to autoregressive image generation that
  is based on two main ingredients. The first is wavelet image coding, which
  allows to tokenize the visual details of an image from coarse to fine details
  by ordering the information starting with the most significant bits of the most
  significant wavelet coefficients. The second is a variant of a language
  transformer whose architecture is re-designed and optimized for token sequences
  in this 'wavelet language'. The transformer learns the significant statistical
  correlations within a token sequence, which are the manifestations of
  well-known correlations between the wavelet subbands at various resolutions. We
  show experimental results with conditioning on the generation process.
paper_ai_keywords: wavelet image coding wavelet coefficients tokenization coarse to fine details language transformer wavelet subbands correlations between the wavelet subbands resolutions conditioning