title: Infinity: Scaling Bitwise AutoRegressive Modeling for High-Resolution
    Image Synthesis
summary: We present Infinity, a Bitwise Visual AutoRegressive Modeling capable of
  generating high-resolution, photorealistic images following language
  instruction. Infinity redefines visual autoregressive model under a bitwise
  token prediction framework with an infinite-vocabulary tokenizer & classifier
  and bitwise self-correction mechanism, remarkably improving the generation
  capacity and details. By theoretically scaling the tokenizer vocabulary size to
  infinity and concurrently scaling the transformer size, our method
  significantly unleashes powerful scaling capabilities compared to vanilla VAR.
  Infinity sets a new record for autoregressive text-to-image models,
  outperforming top-tier diffusion models like SD3-Medium and SDXL. Notably,
  Infinity surpasses SD3-Medium by improving the GenEval benchmark score from
  0.62 to 0.73 and the ImageReward benchmark score from 0.87 to 0.96, achieving a
  win rate of 66%. Without extra optimization, Infinity generates a high-quality
  1024x1024 image in 0.8 seconds, making it 2.6x faster than SD3-Medium and
  establishing it as the fastest text-to-image model. Models and codes will be
  released to promote further exploration of Infinity for visual generation and
  unified tokenizer modeling.
paper_authors._id: 67526cb3067cdbb1447b7879
paper_authors.name: Jian Han
paper_authors._id: 67526cb3067cdbb1447b787a
paper_authors.name: Jinlai Liu
paper_authors._id: 67526cb3067cdbb1447b787b
paper_authors.name: Yi Jiang
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-03-02T20:19:20.042Z
paper_authors._id: 6344dcb1cd37e44d9ed46508
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/6344dcb1cd37e44d9ed46508/J92UKSxKR3iziD2WJfih4.jpeg
paper_authors.fullname: Yi Jiang
paper_authors.type: user
paper_authors.user: JiangYi
paper_authors._id: 67526cb3067cdbb1447b787c
paper_authors.name: Bin Yan
paper_authors._id: 67526cb3067cdbb1447b787d
paper_authors.name: Yuqi Zhang
paper_authors._id: 67526cb3067cdbb1447b787e
paper_authors.name: Zehuan Yuan
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-12-06T17:24:40.351Z
paper_authors._id: 661a80af3557013b638061d5
paper_authors.avatarUrl: /avatars/4c551aeb223e257a5fc45b5b6c7ded49.svg
paper_authors.fullname: Zehuan Yuan
paper_authors.type: user
paper_authors.user: sweetrabor
paper_authors._id: 67526cb3067cdbb1447b787f
paper_authors.name: Bingyue Peng
paper_authors._id: 67526cb3067cdbb1447b7880
paper_authors.name: Xiaobing Liu
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-12-06T17:24:07.640Z
paper_authors._id: 66dbf16d7ec0e5f42175dbcb
paper_authors.avatarUrl: /avatars/d28477ac9f02b633300cd51dea78704f.svg
paper_authors.fullname: liuxiaobing
paper_authors.type: user
paper_authors.user: xiaobinggg
paper_title: Infinity: Scaling Bitwise AutoRegressive Modeling for High-Resolution
    Image Synthesis
paper_summary: We present Infinity, a Bitwise Visual AutoRegressive Modeling capable of
  generating high-resolution, photorealistic images following language
  instruction. Infinity redefines visual autoregressive model under a bitwise
  token prediction framework with an infinite-vocabulary tokenizer & classifier
  and bitwise self-correction mechanism, remarkably improving the generation
  capacity and details. By theoretically scaling the tokenizer vocabulary size to
  infinity and concurrently scaling the transformer size, our method
  significantly unleashes powerful scaling capabilities compared to vanilla VAR.
  Infinity sets a new record for autoregressive text-to-image models,
  outperforming top-tier diffusion models like SD3-Medium and SDXL. Notably,
  Infinity surpasses SD3-Medium by improving the GenEval benchmark score from
  0.62 to 0.73 and the ImageReward benchmark score from 0.87 to 0.96, achieving a
  win rate of 66%. Without extra optimization, Infinity generates a high-quality
  1024x1024 image in 0.8 seconds, making it 2.6x faster than SD3-Medium and
  establishing it as the fastest text-to-image model. Models and codes will be
  released to promote further exploration of Infinity for visual generation and
  unified tokenizer modeling.
paper_ai_keywords: Bitwise Visual AutoRegressive Modeling bitwise token prediction framework infinite-vocabulary tokenizer & classifier bitwise self-correction mechanism autoregressive text-to-image models diffusion models SD3-Medium SDXL GenEval benchmark score ImageReward benchmark score transformer size vanilla VAR