InsightTok

InsightTok is a discrete visual tokenizer designed to improve the fidelity of text and faces, two of the most challenging yet perceptually important structures in autoregressive image generation.

It was introduced in the paper InsightTok: Improving Text and Face Fidelity in Discrete Tokenization for Autoregressive Image Generation.

Model Details

Property Value
Downsampling rate 16×
Codebook size 16,384
Latent dimension 256
Number of parameters 426M

Performance

InsightTok achieves strong text and face reconstruction quality while maintaining a compact discrete representation.

Usage

Please refer to our GitHub repository.

Citation

@article{yue2026insighttok,
  title={InsightTok: Improving Text and Face Fidelity in Discrete Tokenization for Autoregressive Image Generation},
  author={Yue, Yang and Wei, Fangyun and He, Tianyu and Zhao, Jinjing and Ni, Zanlin and Liu, Zeyu and Guo, Jiayi and Shi, Lei and Dong, Yue and Chen, Li and Li, Ji and Huang, Gao and Chen, Dong},
  journal={arXiv preprint arXiv:TODO},
  year={2026}
}
Downloads last month

-

Downloads are not tracked for this model. How to track
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support