---
license: apache-2.0
---



<br>

# ViG Model Card

## Model Details

ViG is a generic backbone trained on the ImageNet-1K dataset for vision tasks.

- **Developed by:** [HUST](https://english.hust.edu.cn/), [Horizon Robotics](https://en.horizon.cc/)
- **Model type:** A generic vision backbone based on the Gated Linear Attention (GLA) architecture.
- **License:** Non-commercial license


### Model Sources

- **Repository:** https://github.com/hustvl/ViG
- **Paper:** https://arxiv.org/abs/2405.18425

## Uses

The primary use of ViG is research on vision tasks, e.g., classification, segmentation, detection, and instance segmentation, with an GLA-based backbone.
The primary intended users of the model are researchers and hobbyists in computer vision, machine learning, and artificial intelligence.


## Training Details

ViG is pretrained on ImageNet-1K with classification supervision.
The training data is around 1.3M images from [ImageNet-1K dataset](https://www.image-net.org/challenges/LSVRC/2012/).
See more details in this [paper](https://arxiv.org/abs/2405.18425).

## Evaluation

ViG is evaluated on ImageNet-1K val set, more details can be found in this [paper](https://arxiv.org/abs/2405.18425).

## Additional Information

## Citation Information

```
 @article{vig,
  title={ViG: Linear-complexity Visual Sequence Learning with Gated Linear Attention},
  author={Bencheng Liao and Xinggang Wang and Lianghui Zhu and Qian Zhang and Chang Huang},
  journal={arXiv preprint arXiv:2405.18425},
  year={2024}
}
```