SwinFSR: Stereo Image Super-Resolution using SwinIR and Frequency Domain Knowledge
Theses
Overview
Research
View All
Overview
abstract
Stereo Image Super-Resolution (stereoSR) has attracted significant attention in recent
years due to the extensive deployment of dual cameras in mobile phones, autonomous
vehicles and robots. In this work, we propose a new StereoSR method, named SwinFSR,
based on an extension of SwinIR, originally designed for single image restoration, and the
frequency domain knowledge obtained by the Fast Fourier Convolution (FFC). Specifically, to effectively gather global information, we modify the Residual Swin Transformer
blocks (RSTBs) in SwinIR by explicitly incorporating the frequency domain knowledge
using the FFC and employing the resulting residual Swin Fourier Transformer blocks
(RSFTBlocks) for feature extraction. Besides, for the efficient and accurate fusion of
stereo views, we propose a new cross-attention module referred to as RCAM, which
achieves highly competitive performance while requiring less computational cost than
the state-of-the-art cross-attention modules. Extensive experimental results and ablation studies demonstrate the effectiveness and efficiency of our proposed SwinFSR.
iv
