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We introduce optical Flow transFormer, dubbed as FlowFormer, a transformer-based neural network architecture for learning optical flow.
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Sun, D., Yang, X., Liu, M.Y., Kautz, J.: Pwc-net: Cnns for optical flow using pyramid, warping, and cost volume. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 8934–8943 (2018)
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Sun, D., Yang, X., Liu, M.Y., Kautz, J.: Models matter, so does training: An empirical study of cnns for optical flow estimation. IEEE transactions on pattern analysis and machine intelligence 42
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Yin, Z., Darrell, T., Yu, F.: Hierarchical discrete distribution decomposition for match density estimation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 6044–6053 (2019)
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Gao, C., Saraf, A., Huang, J.B., Kopf, J.: Flow-edge guided video completion. In: European Conference on Computer Vision. pp. 713–729. Springer (2020)
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Hofinger, M., Bulò, S.R., Porzi, L., Knapitsch, A., Pock, T., Kontschieder, P.: Improving optical flow on a pyramid level. In: European Conference on Computer Vision. pp. 770–786. Springer (2020)
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2020
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Hui, T.W., Tang, X., Loy, C.C.: A lightweight optical flow cnn—revisiting data fidelity and regularization. IEEE transactions on pattern analysis and machine intelligence 43
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2021
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Jiang, S., Lu, Y., Li, H., Hartley, R.: Learning optical flow from a few matches. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 16592–16600 (2021)
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Sun, D., Vlasic, D., Herrmann, C., Jampani, V., Krainin, M., Chang, H., Zabih, R., Freeman, W.T., Liu, C.: Autoflow: Learning a better training set for optical flow. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 10093–10102 (2021)
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Sun, J., Shen, Z., Wang, Y., Bao, H., Zhou, X.: Loftr: Detector-free local feature matching with transformers. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 8922–8931 (2021)
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Xu, H., Yang, J., Cai, J., Zhang, J., Tong, X.: High-resolution optical flow from 1d attention and correlation. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 10498–10507 (2021)
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Zhang, F., Woodford, O.J., Prisacariu, V.A., Torr, P.H.: Separable flow: Learning motion cost volumes for optical flow estimation. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 10807–10817 (2021)
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2022
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Yang, L., Xu, Y., Yuan, C., Liu, W., Li, B., Hu, W.: Improving visual grounding with visual-linguistic verification and iterative reasoning. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 9499–9508 (2022)
2022
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