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TESA: Tensor Element Self-Attention via Matricization.

, , , and . CVPR, page 13942-13951. Computer Vision Foundation / IEEE, (2020)

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Linear Complexity Self-Attention With $3rd$3 rd Order Polynomials., , , , , , , and . IEEE Trans. Pattern Anal. Mach. Intell., 45 (11): 12726-12737 (November 2023)Online learning and fusion of orientation appearance models for robust rigid object tracking., , , , and . FG, page 1-8. IEEE Computer Society, (2013)Poly-NL: Linear Complexity Non-local Layers With 3rd Order Polynomials., , , , , and . ICCV, page 10498-10508. IEEE, (2021)NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results., , , , , , , , , and 80 other author(s). CVPR Workshops, page 2077-2088. Computer Vision Foundation / IEEE, (2020)Deep Mixture of MRFs for Human Pose Estimation., , and . ACCV (3), volume 11363 of Lecture Notes in Computer Science, page 717-733. Springer, (2018)Reconstructing the Noise Manifold for Image Denoising., , , , and . CoRR, (2020)Pixel Adaptive Filtering Units., , , , and . CoRR, (2019)Poly-NL: Linear Complexity Non-local Layers with Polynomials., , , , , and . CoRR, (2021)TESA: Tensor Element Self-Attention via Matricization., , , and . CVPR, page 13942-13951. Computer Vision Foundation / IEEE, (2020)Reconstructing the Noise Variance Manifold for Image Denoising., , , , and . ECCV (9), volume 12354 of Lecture Notes in Computer Science, page 622-639. Springer, (2020)