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Attention within windows has been widely explored in vision transformers to balance the performance, computation complexity, and memory footprint.
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He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 770–778 (2016)
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Dai, J., Qi, H., Xiong, Y., Li, Y., Zhang, G., Hu, H., Wei, Y.: Deformable convolutional networks. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV). pp. 764–773 (2017)
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He, K., Gkioxari, G., Dollár, P., Girshick, R.: Mask r-cnn. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV). pp. 2961–2969 (2017)
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Lin, T.Y., Goyal, P., Girshick, R., He, K., Dollár, P.: Focal loss for dense object detection. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV). pp. 2980–2988 (2017)
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Cai, Z., Vasconcelos, N.: Cascade r-cnn: Delving into high quality object detection. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 6154–6162 (2018)
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Loshchilov, I., Hutter, F.: Decoupled weight decay regularization. In: International Conference on Learning Representations (2018)
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Xiao, T., Liu, Y., Zhou, B., Jiang, Y., Sun, J.: Unified perceptual parsing for scene understanding. In: Proceedings of the European Conference on Computer Vision (ECCV). pp. 418–434 (2018)
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Cai, Z., Vasconcelos, N.: Cascade r-cnn: High quality object detection and instance segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2019)
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Lin, C., Guo, M., Li, C., Yuan, X., Wu, W., Yan, J., Lin, D., Ouyang, W.: Online hyper-parameter learning for auto-augmentation strategy. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV). pp. 6579–6588 (2019)
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Yun, S., Han, D., Oh, S.J., Chun, S., Choe, J., Yoo, Y.: Cutmix: Regularization strategy to train strong classifiers with localizable features. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV). pp. 6023–6032 (2019)
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Zhu, X., Hu, H., Lin, S., Dai, J.: Deformable convnets v2: More deformable, better results. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 9308–9316 (2019)
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2020
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Jing, Y., Liu, X., Ding, Y., Wang, X., Ding, E., Song, M., Wen, S.: Dynamic instance normalization for arbitrary style transfer. In: AAAI (2020)
2020
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Chen, Z., Zhu, Y., Zhao, C., Hu, G., Zeng, W., Wang, J., Tang, M.: Dpt: Deformable patch-based transformer for visual recognition. In: Proceedings of the 29th ACM International Conference on Multimedia. pp. 2899–2907 (2021)
2021
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Chu, X., Tian, Z., Wang, Y., Zhang, B., Ren, H., Wei, X., Xia, H., Shen, C.: Twins: Revisiting the design of spatial attention in vision transformers. In: Advances in Neural Information Processing Systems (2021)
2021
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2021
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Wang, W., Xie, E., Li, X., Fan, D.P., Song, K., Liang, D., Lu, T., Luo, P., Shao, L.: Pvtv2: Improved baselines with pyramid vision transformer (2021)
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Wang, W., Xie, E., Li, X., Fan, D.P., Song, K., Liang, D., Lu, T., Luo, P., Shao, L.: Pyramid vision transformer: A versatile backbone for dense prediction without convolutions. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV). pp. 568–578 (2021)
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Xu, Y., ZHANG, Q., Zhang, J., Tao, D.: ViTAE: Vision transformer advanced by exploring intrinsic inductive bias. In: Advances in Neural Information Processing Systems (2021)
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2021
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Dai, Z., Liu, H., Le, Q.V., Tan, M.: Coatnet: Marrying convolution and attention for all data sizes. In: Advances in Neural Information Processing Systems (2021)
2021
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2021
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Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., Uszkoreit, J., Houlsby, N.: An image is worth 16x16 words: Transformers for image recognition at scale. In: International Conference on Learning Representations (2021)
2021
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2021
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2021
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2021
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Han, K., Xiao, A., Wu, E., Guo, J., Xu, C., Wang, Y.: Transformer in transformer. Advances in Neural Information Processing Systems 34
2021
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2021
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Yang, J., Li, C., Zhang, P., Dai, X., Xiao, B., Yuan, L., Gao, J.: Focal attention for long-range interactions in vision transformers. In: Advances in Neural Information Processing Systems (2021)
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Yuan, L., Chen, Y., Wang, T., Yu, W., Shi, Y., Jiang, Z.H., Tay, F.E., Feng, J., Yan, S.: Tokens-to-token vit: Training vision transformers from scratch on imagenet. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV). pp. 558–567 (2021)
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Zhang, P., Dai, X., Yang, J., Xiao, B., Yuan, L., Zhang, L., Gao, J.: Multi-scale vision longformer: A new vision transformer for high-resolution image encoding. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV). pp. 2998–3008 (October 2021)
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Zhang, Q., Yang, Y.B.: Rest: An efficient transformer for visual recognition. Advances in Neural Information Processing Systems 34
2021
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Zhu, X., Su, W., Lu, L., Li, B., Wang, X., Dai, J.: Deformable detr: Deformable transformers for end-to-end object detection. In: International Conference on Learning Representations (2021)
2021
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Chen, C.F., Panda, R., Fan, Q.: Regionvit: Regional-to-local attention for vision transformers. In: International Conference on Learning Representations (2022)
2022
Closest in time.
Wang, W., Yao, L., Chen, L., Lin, B., Cai, D., He, X., Liu, W.: Crossformer: A versatile vision transformer hinging on cross-scale attention. In: International Conference on Learning Representations (2022)
2022
Closest in time.
Wu, S., Wu, T., Tan, H., Guo, G.: Pale transformer: A general vision transformer backbone with pale-shaped attention. In: Proceedings of the AAAI Conference on Artificial Intelligence (2022)
2022
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Xia, Z., Pan, X., Song, S., Li, L.E., Huang, G.: Vision transformer with deformable attention (2022)
2022
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2022
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Yang, Z., Liu, D., Wang, C., Yang, J., Tao, D.: Modeling image composition for complex scene generation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 7764–7773 (2022)
2022
Closest in time.