Use HF papers (#38184)
* Use hf papers * Hugging Face papers * doi to hf papers * style
This commit is contained in:
committed by
GitHub
parent
1031ed5166
commit
de24fb63ed
@@ -18,7 +18,7 @@ specific language governing permissions and limitations under the License.
|
||||
|
||||
## Overview
|
||||
|
||||
The ViTMatte model was proposed in [Boosting Image Matting with Pretrained Plain Vision Transformers](https://arxiv.org/abs/2305.15272) by Jingfeng Yao, Xinggang Wang, Shusheng Yang, Baoyuan Wang.
|
||||
The ViTMatte model was proposed in [Boosting Image Matting with Pretrained Plain Vision Transformers](https://huggingface.co/papers/2305.15272) by Jingfeng Yao, Xinggang Wang, Shusheng Yang, Baoyuan Wang.
|
||||
ViTMatte leverages plain [Vision Transformers](vit) for the task of image matting, which is the process of accurately estimating the foreground object in images and videos.
|
||||
|
||||
The abstract from the paper is the following:
|
||||
@@ -31,7 +31,7 @@ The original code can be found [here](https://github.com/hustvl/ViTMatte).
|
||||
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/vitmatte_architecture.png"
|
||||
alt="drawing" width="600"/>
|
||||
|
||||
<small> ViTMatte high-level overview. Taken from the <a href="https://arxiv.org/abs/2305.15272">original paper.</a> </small>
|
||||
<small> ViTMatte high-level overview. Taken from the <a href="https://huggingface.co/papers/2305.15272">original paper.</a> </small>
|
||||
|
||||
## Resources
|
||||
|
||||
|
||||
Reference in New Issue
Block a user