This repository contains the official PyTorch implementation of our research papers for SOTA computer vision architectures.
We provide an paper list and their project folders in this GitHub repository.
| Year | Venue | Title | Paper | Project |
|---|---|---|---|---|
| 2023 | ICCV | Gramian Attention Heads are Strong yet Efficient Vision Learners | GA | |
| 2025 | WACV | Enriching Local Patterns with Multi-Token Attention for Broad-Sight Neural Networks | TBD | MAP |
@inproceedings{ryu2023gramian,
title={Gramian Attention Heads are Strong yet Efficient Vision Learners},
author={Ryu, Jongbin and Han, Dongyoon and Lim, Jongwoo},
booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
pages={5841--5851},
year={2023}
}
This repository is released under the Apache 2.0 license as found in the LICENSE file.