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license: apache-2.0 |
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# ViG Model Card |
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## Model Details |
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ViG is a generic backbone trained on the ImageNet-1K dataset for vision tasks. |
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- **Developed by:** [HUST](https://english.hust.edu.cn/), [Horizon Robotics](https://en.horizon.cc/) |
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- **Model type:** A generic vision backbone based on the Gated Linear Attention (GLA) architecture. |
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- **License:** Non-commercial license |
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### Model Sources |
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- **Repository:** https://github.com/hustvl/ViG |
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- **Paper:** https://arxiv.org/abs/2405.18425 |
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## Uses |
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The primary use of ViG is research on vision tasks, e.g., classification, segmentation, detection, and instance segmentation, with an GLA-based backbone. |
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The primary intended users of the model are researchers and hobbyists in computer vision, machine learning, and artificial intelligence. |
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## Training Details |
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ViG is pretrained on ImageNet-1K with classification supervision. |
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The training data is around 1.3M images from [ImageNet-1K dataset](https://www.image-net.org/challenges/LSVRC/2012/). |
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See more details in this [paper](https://arxiv.org/abs/2405.18425). |
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## Evaluation |
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ViG is evaluated on ImageNet-1K val set, more details can be found in this [paper](https://arxiv.org/abs/2405.18425). |
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## Additional Information |
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## Citation Information |
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``` |
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@article{vig, |
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title={ViG: Linear-complexity Visual Sequence Learning with Gated Linear Attention}, |
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author={Bencheng Liao and Xinggang Wang and Lianghui Zhu and Qian Zhang and Chang Huang}, |
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journal={arXiv preprint arXiv:2405.18425}, |
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year={2024} |
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} |
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``` |
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