Sep 19, 2024 · We propose a multi-group window self-attention (MGWSA), which achieves self-attention calculation on different groups of features via different window sizes.

To implement a lightweight convolutional operation that assists self-attention for local feature extraction, we propose a residual blueprint separable ...

Sep 22, 2024 · We propose a multi-group window self-attention (MGWSA), which achieves self-attention calculation on different groups of features via different window sizes.

To implement a lightweight convolutional operation that assists self-attention for local feature extraction, we propose a residual blueprint separable ...

In this paper, we propose a new lightweight SR network, namely Blueprint Separable Residual Network (BSRN), which improves the network's efficiency from two ...

Lightweight super-resolution via multi-group window self-attention and residual blueprint separable convolution. Article. Full-text available. Sep 2024.

Aug 8, 2024 · We propose a lightweight Residual and Detail self-attention Network (RDNet) for infrared image super-resolution.

Jun 15, 2024 · This paper proposes an efficient model (BCRN) based on BSConv and the ConvNeXt residual structure for single image super-resolution, which ...

Sep 26, 2024 · In this work, we propose a lightweight convolution-based method with linear complexity for local-global adaptive modeling called the Linear- ...

This paper proposes Blueprint Separable Residual Network (BSRN), a model containing two efficient designs, one of which is the usage of blueprint separable ...