--- pipeline_tag: image-feature-extraction --- # Image Tokenizer Needs Post-Training This repository contains the official implementation and checkpoints for the paper [Image Tokenizer Needs Post-Training](https://huggingface.co/papers/2509.12474). Project page: https://qiuk2.github.io/works/RobusTok/index.html Code: https://github.com/qiuk2/RobusTok
Teaser
--- ## TL;DR We present RobusTok, a new image tokenizer with a two-stage training scheme: Main training → constructs a robust latent space. Post-training → aligns the generator’s latent distribution with its image space. ## Key highlights of Post-Training - 🚀 **Better generative quality**: gFID 1.60 → 1.36. - 🔑 **Generalizability**: applicable to both autoregressive & diffusion models. - ⚡ **Efficiency**: strong results with only ~400M generative models. --- ## Model Zoo | Generator \ Tokenizer | RobusTok w/o. P.T([weights](https://huggingface.co/qiuk6/RobusTok/resolve/main/main-train.pt?download=true)) | RobusTok w/. P.T ([weights](https://huggingface.co/qiuk6/RobusTok/resolve/main/post-train.pt?download=true)) | |---|---:|---:| | Base ([weights](https://huggingface.co/qiuk6/RobusTok/resolve/main/rar_b.bin?download=true)) | gFID = 1.83 | gFID = 1.60 | | Large ([weights](https://huggingface.co/qiuk6/RobusTok/resolve/main/rar_l.bin?download=true)) | gFID = 1.60 | gFID = 1.36 | --- ## Usage For detailed installation, training, and inference instructions, please refer to the [GitHub repository](https://github.com/qiuk2/RobusTok). --- ## Visualization
vis

visualization of 256×256 image generation before (top) and after (bottom) post-training. Three improvements are observed: (a) OOD mitigation, (b) Color fidelity, (c) detail refinement.

--- ## Citation If our work assists your research, feel free to give us a star ⭐ or cite us using ```bibtex @misc{qiu2025imagetokenizerneedsposttraining, title={Image Tokenizer Needs Post-Training}, author={Kai Qiu and Xiang Li and Hao Chen and Jason Kuen and Xiaohao Xu and Jiuxiang Gu and Yinyi Luo and Bhiksha Raj and Zhe Lin and Marios Savvides}, year={2025}, eprint={2509.12474}, archivePrefix={arXiv}, primaryClass={cs.CV}, url={https://arxiv.org/abs/2509.12474}, } ```