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---
license: apache-2.0
datasets:
- timbrooks/instructpix2pix-clip-filtered
language:
- en
---
# Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation
### CVPR 2025 (Highlight)
[Project Page](https://bolinlai.github.io/projects/InstaManip/) | [Paper](https://openaccess.thecvf.com/content/CVPR2025/papers/Lai_Unleashing_In-context_Learning_of_Autoregressive_Models_for_Few-shot_Image_Manipulation_CVPR_2025_paper.pdf) | [Code](https://github.com/BolinLai/InstaManip)
[Bolin Lai](https://bolinlai.github.io/), [Felix Juefei-Xu](https://xujuefei.com/), [Miao Liu](https://aptx4869lm.github.io/), [Xiaoliang Dai](https://sites.google.com/view/xiaoliangdai/), [Nikhil Mehta](https://hockeybro12.github.io/), [Chenguang Zhu](https://cs.stanford.edu/~cgzhu/), [Zeyi Huang](https://oodbag.github.io/), [James M. Rehg](https://rehg.org/), [Sangmin Lee](https://sites.google.com/view/sangmin-lee), [Ning Zhang](https://n-zhang.github.io/), [Tong Xiao](http://xiaotong.me/)
<img src="https://bolinlai.github.io/projects/InstaManip/figures/teaser.png"/>
This repo is the model weights for our paper "Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation".
There are four models released in this repo.
- InstaManip-17B-1shot: model trained specifically for 1-shot image manipulation.
- InstaManip-17B-2shot: model trained specifically for 2-shot image manipulation.
- InstaManip-17B-3shot: model trained specifically for 3-shot image manipulation.
- InstaManip-17B-dynamic: model trained for arbitrary amount of exemplar image pairs.
Please refer to the code on [github](https://github.com/BolinLai/InstaManip) for detailed instructions on how to use it.
If you find our paper helpful to your work, please cite with this BibTex.
```BibTex
@inproceedings{lai2025unleashing,
title={Unleashing in-context learning of autoregressive models for few-shot image manipulation},
author={Lai, Bolin and Juefei-Xu, Felix and Liu, Miao and Dai, Xiaoliang and Mehta, Nikhil and Zhu, Chenguang and Huang, Zeyi and Rehg, James M and Lee, Sangmin and Zhang, Ning and Xiao, Tong},
booktitle={Proceedings of the Computer Vision and Pattern Recognition Conference},
pages={18346--18357},
year={2025}
}
``` |