@ -1,36 +1,50 @@
# SparK✨: The first successful BERT-style pre-training on any convolutional networks [](https://arxiv.org/abs/2301.03580), ICLR'23 Spotlight
Official implementation of "Designing BERT for Convolutional Networks: ** *Spar***se and Hierarchical Mas***k***ed Modeling".
# SparK: The first successful BERT-style pre-training on any convolutional networks [](https://openreview.net/forum?id=NRxydtWup1S) [](https://arxiv.org/abs/2301.03580)
Official implementation of [Designing BERT for Convolutional Networks: ***Spar***se and Hierarchical Mas***k***ed Modeling ](https://arxiv.org/abs/2301.03580 ).
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[[`arXiv` ](https://arxiv.org/abs/2301.03580 )]
[[`pdf` ](https://arxiv.org/pdf/2301.03580.pdf )]
[[`state-of-the-art self-supervised convnet` ](https://paperswithcode.com/sota/self-supervised-image-classification-on-1?tag_filter=17?p=designing-bert-for-convolutional-networks )]
[[`bibtex` ](https://github.com/keyu-tian/SparK#citation )]
[](https://www.reddit.com/r/MachineLearning/comments/10ix0l1/r_iclr2023_spotlight_the_first_bertstyle/)
[](https://twitter.com/keyutian/status/1616606179144380422)
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[](https://paperswithcode.com/sota/self-supervised-image-classification-on-1?tag_filter=17&p=designing-bert-for-convolutional-networks)
[](https://openreview.net/forum?id=NRxydtWup1S)
[](https://arxiv.org/abs/2301.03580)
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<!-- [[`pdf` ](https://arxiv.org/pdf/2301.03580.pdf )] -->
<!-- [[`bibtex` ](https://github.com/keyu-tian/SparK#citation )] -->
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<!-- [[`Bytedance` ](https://mp.weixin.qq.com/s/Ak1CeeG83sgO0Wf8KgEIQQ )] -->
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[[`📹Talk @TechBeat(将门)` ](https://www.techbeat.net/talk-info?id=758 )]
[[`ReadPaper` ](https://readpaper.com/paper/4710371282714116097 )]
[[`Synced` ](https://syncedreview.com/2023/01/19/bert-style-pretraining-on-convnets-peking-u-bytedance-oxford-us-sparse-masked-modelling-with-hierarchy-leads-the-way/ )]
[[`The Gradient` ](https://thegradientpub.substack.com/p/update-42-ai-news-editors-make-mistakes )]
[[`QbitAI` ](https://www.qbitai.com/2023/02/42109.html )]
[[`Bytedance` ](https://mp.weixin.qq.com/s/Ak1CeeG83sgO0Wf8KgEIQQ )]
[[`DeepAI` ](https://deepai.org/publication/designing-bert-for-convolutional-networks-sparse-and-hierarchical-masked-modeling )]
[[`Reddit` ](https://www.reddit.com/r/MachineLearning/comments/10ix0l1/r_iclr2023_spotlight_the_first_bertstyle/ )]
[[`Twitter` ](https://twitter.com/keyutian/status/1616606179144380422 )]
[[`TheGradient` ](https://thegradientpub.substack.com/p/update-42-ai-news-editors-make-mistakes )]
[[`CVer` ](https://zhuanlan.zhihu.com/p/598056871 )]
[[`Synced(机器之心)` ](https://syncedreview.com/2023/01/19/bert-style-pretraining-on-convnets-peking-u-bytedance-oxford-us-sparse-masked-modelling-with-hierarchy-leads-the-way/ )]
[[`QbitAI(量子位)` ](https://www.qbitai.com/2023/02/42109.html )]
[[`BAAI(智源)` ](https://hub.baai.ac.cn/view/23360 )]
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## 🔥 News
- The share on [TechBeat (将门创投) ](https://www.techbeat.net/talk-info?id=758 ) is scheduled on **Mar. 16th (UTC+0 12am, UTC+8 8pm)** too! [[`Recorded Video` ](https://www.techbeat.net/talk-info?id=758 )]
- We are honored to be invited by Synced ("机器之心机动组 视频号" on WeChat) to give a talk about SparK on **Feb. 27th (UTC+0 11am, UTC+8 7pm)** , welcome! [[`Recorded Video` ](https://www.bilibili.com/video/BV1J54y1u7U3/ )]
- The share on [TechBeat (将门创投) ](https://www.techbeat.net/talk-info?id=758 ) is scheduled on **Mar. 16th (UTC+0 12am, UTC+8 8pm)** too! [[`📹 Recorded Video` ](https://www.techbeat.net/talk-info?id=758 )]
- We are honored to be invited by Synced ("机器之心机动组 视频号" on WeChat) to give a talk about SparK on **Feb. 27th (UTC+0 11am, UTC+8 7pm)** , welcome! [[`📹 Recorded Video` ](https://www.bilibili.com/video/BV1J54y1u7U3/ )]
- This work got accepted to ICLR 2023 as a Spotlight (notable-top-25%).
@ -116,15 +130,8 @@ See [PRETRAIN.md](PRETRAIN.md) to pre-train models on ImageNet-1k.
We referred to these useful codebases:
- [BEiT ](https://github.com/microsoft/unilm/tree/master/beit )
- [MAE ](https://github.com/facebookresearch/mae )
- [ConvNeXt ](https://github.com/facebookresearch/ConvNeXt )
We also appreciate these elegant frameworks:
- [timm ](https://github.com/rwightman/pytorch-image-models )
- [MoCoV2 ](https://github.com/facebookresearch/moco )
- [Detectron2 ](https://github.com/facebookresearch/detectron2 ) and [MMDetection ](https://github.com/open-mmlab/mmdetection )
- [BEiT ](https://github.com/microsoft/unilm/tree/master/beit ), [MAE ](https://github.com/facebookresearch/mae ), [ConvNeXt ](https://github.com/facebookresearch/ConvNeXt )
- [timm ](https://github.com/rwightman/pytorch-image-models ), [MoCoV2 ](https://github.com/facebookresearch/moco ), [Detectron2 ](https://github.com/facebookresearch/detectron2 ), [MMDetection ](https://github.com/open-mmlab/mmdetection )
@ -134,7 +141,7 @@ This project is under the MIT license. See [LICENSE](LICENSE) for more details.
## Citation
If you found this project useful, please consider adding a star ⭐, or citing us 📖:
If you found this project useful, you may consider staring ⭐, or citing us 📖:
```
@Article {tian2023designing,
author = {Keyu Tian and Yi Jiang and Qishuai Diao and Chen Lin and Liwei Wang and Zehuan Yuan},
keyu tian
2 years ago