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HiT-SR: Hierarchical Transformer for Efficient Image Super-Resolution

8 Jul 2024arXiv:2407.05878archive 2025-07-28

Xiang Zhang, Yulun Zhang, Fisher Yu

Transformers have exhibited promising performance in computer vision tasks including image super-resolution (SR). However, popular transformer-based SR methods often employ window self-attention with quadratic computational complexity to window sizes, resulting in fixed small windows with limited receptive fields. In this paper, we present a general strategy to convert transformer-based SR networks to hierarchical transformers (HiT-SR), boosting SR performance with multi-scale features while maintaining an efficient design. Specifically, we first replace the commonly used fixed small windows with expanding hierarchical windows to aggregate features at different scales and establish long-range dependencies. Considering the intensive computation required for large windows, we further design a spatial-channel correlation method with linear complexity to window sizes, efficiently gathering spatial and channel information from hierarchical windows. Extensive experiments verify the effectiveness and efficiency of our HiT-SR, and our improved versions of SwinIR-Light, SwinIR-NG, and SRFormer-Light yield state-of-the-art SR results with fewer parameters, FLOPs, and faster speeds (∼7×).

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Tasks

Image Super-ResolutionSuper-Resolution

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Image Super-Resolution Set14 - 4x upscaling HiT-SRF PSNR 28.87 #40 of 104 Archive leaderboard report
Image Super-Resolution Set14 - 4x upscaling HiT-SRF SSIM 0.7880 #40 of 104 Archive leaderboard report
Image Super-Resolution Set14 - 4x upscaling HiT-SiR PSNR 28.84 #43 of 104 Archive leaderboard report
Image Super-Resolution Set14 - 4x upscaling HiT-SiR SSIM 0.7873 #43 of 104 Archive leaderboard report
Image Super-Resolution Set14 - 4x upscaling HiT-SNG PSNR 28.83 #44 of 104 Archive leaderboard report
Image Super-Resolution Set14 - 4x upscaling HiT-SNG SSIM 0.7873 #44 of 104 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

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