| | --- |
| | license: apache-2.0 |
| | pipeline_tag: image-to-image |
| | arxiv: 2509.23774 |
| | tags: |
| | - super-resolution |
| | - generative-models |
| | - quantization |
| | - pytorch |
| | --- |
| | # TVQRAP: Texture Vector-Quantization and Reconstruction Aware Prediction for Generative Super-Resolution (ICLR 2026) |
| |
|
| | [paper](https://arxiv.org/abs/2509.23774) | [code](https://github.com/CVL-UESTC/TVQ-RAP) |
| |
|
| | If you find our work useful, please consider citing: |
| | ```bibtex |
| | @article{li2025texture, |
| | title={Texture Vector-Quantization and Reconstruction Aware Prediction for Generative Super-Resolution}, |
| | author={Li, Qifan and Zou, Jiale and Zhang, Jinhua and Long, Wei and Zhou, Xingyu and Gu, Shuhang}, |
| | journal={arXiv preprint arXiv:2509.23774}, |
| | year={2025} |
| | } |
