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Rethinking Multi-Scale Representations in Deep Deraining Transformer
Proceedings of the AAAI Conference on Artificial IntelligenceExisting Transformer-based image deraining methods depend mostly on fixed single-input single-output U-Net architecture. In fact, this not only neglects the potentially explicit information from multiple image scales, but also lacks the capability of exploring the complementary implicit information across different scales.
Hongming Chen 0004 +3 more
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Implicit Neural Representation with Multi-Scale Sine Activation
Proceedings of the AAAI Conference on Artificial IntelligenceImplicit Neural Representations (INRs) have become a powerful paradigm for modeling continuous signals in computer vision, graphics, and scientific computing. However, multilayer perceptrons (MLPs) generally suffer from severe spectral bias, which limits their ability to accurately model high-frequency details and multi-scale structures.
Jufeng Han +7 more
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Multi-scale discriminant representation for generic palmprint recognition
Neural Computing and Applications, 2023Lingli Yu, Qian Yi, Kaijun Zhou
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Bridging Multi-Scale Context-Aware Representation for Object Detection
IEEE Transactions on Circuits and Systems for Video Technology, 2023Boying Wang, Ruyi Ji, Libo Zhang
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Multi-Scale Representation Learning on Hypergraph for 3D Shape Retrieval and Recognition
IEEE Transactions on Image Processing, 2021Junjie Bai, Biao Gong, Yining Zhao
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Multi-focus image fusion based on multi-scale sparse representation
Journal of Visual Communication and Image Representation, 2021Xiaole Ma, Shaohai Hu
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Multi-Scale Compositional Constraints for Representation Learning on Videos
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023Georgios Paraskevopoulos +3 more
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