Infinity: Scaling Bitwise AutoRegressive Modeling for High-Resolution
  Image Synthesis
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.
67526cb3067cdbb1447b7879
Jian Han
67526cb3067cdbb1447b787a
Jinlai Liu
67526cb3067cdbb1447b787b
Yi Jiang
claimed_verified
2025-03-02T20:19:20.042Z
6344dcb1cd37e44d9ed46508
https://cdn-avatars.huggingface.co/v1/production/uploads/6344dcb1cd37e44d9ed46508/J92UKSxKR3iziD2WJfih4.jpeg
Yi Jiang
user
JiangYi
67526cb3067cdbb1447b787c
Bin Yan
67526cb3067cdbb1447b787d
Yuqi Zhang
67526cb3067cdbb1447b787e
Zehuan Yuan
admin_assigned
2024-12-06T17:24:40.351Z
661a80af3557013b638061d5
/avatars/4c551aeb223e257a5fc45b5b6c7ded49.svg
Zehuan Yuan
user
sweetrabor
67526cb3067cdbb1447b787f
Bingyue Peng
67526cb3067cdbb1447b7880
Xiaobing Liu
admin_assigned
2024-12-06T17:24:07.640Z
66dbf16d7ec0e5f42175dbcb
/avatars/d28477ac9f02b633300cd51dea78704f.svg
liuxiaobing
user
xiaobinggg
Infinity: Scaling Bitwise AutoRegressive Modeling for High-Resolution
  Image Synthesis
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.
Infinity, a Bitwise Visual AutoRegressive Model, achieves high-resolution, photorealistic image generation from language instructions, surpassing top-tier diffusion models in speed and quality.
Bitwise Visual AutoRegressive Modeling bitwise token prediction framework infinite-vocabulary tokenizer bitwise self-correction mechanism transformer autoregressive text-to-image models diffusion models SD3-Medium SDXL GenEval benchmark ImageReward benchmark