Papers › Learning Parallax Attention for Stereo Image Super-Resolution

Learning Parallax Attention for Stereo Image Super-Resolution

14 Mar 2019CVPR 2019 6arXiv:1903.05784archive 2025-07-28

Longguang Wang, Yingqian Wang, Zhengfa Liang, Zaiping Lin, Jungang Yang, Wei An, Yulan Guo

Stereo image pairs can be used to improve the performance of super-resolution (SR) since additional information is provided from a second viewpoint. However, it is challenging to incorporate this information for SR since disparities between stereo images vary significantly. In this paper, we propose a parallax-attention stereo superresolution network (PASSRnet) to integrate the information from a stereo image pair for SR. Specifically, we introduce a parallax-attention mechanism with a global receptive field along the epipolar line to handle different stereo images with large disparity variations. We also propose a new and the largest dataset for stereo image SR (namely, Flickr1024). Extensive experiments demonstrate that the parallax-attention mechanism can capture correspondence between stereo images to improve SR performance with a small computational and memory cost. Comparative results show that our PASSRnet achieves the state-of-the-art performance on the Middlebury, KITTI 2012 and KITTI 2015 datasets.

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augumentation LongguangWang/PASSRnet/utils.py official repository unverified MIT (permissive) · 10a6077497d004e2 · report
cal_psnr LongguangWang/PASSRnet/utils.py official repository unverified MIT (permissive) · 653c5ce68e31bd3b · report
morphologic_process LongguangWang/PASSRnet/models.py official repository unverified MIT (permissive) · 6fec1ba187785c2d · report
toTensor LongguangWang/PASSRnet/utils.py official repository unverified MIT (permissive) · 8c87c9a3ae4389f4 · report

Tasks

Image Super-ResolutionStereo Image Super-ResolutionSuper-Resolution

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Image Super-Resolution KITTI 2012 - 2x upscaling PASSRnet PSNR 30.65 #1 of 1 Archive leaderboard report
Image Super-Resolution KITTI 2012 - 4x upscaling PASSRnet PSNR 26.26 #1 of 1 Archive leaderboard report
Image Super-Resolution KITTI 2015 - 2x upscaling PASSRnet PSNR 29.78 #1 of 1 Archive leaderboard report
Image Super-Resolution KITTI 2015 - 4x upscaling PASSRnet PSNR 25.43 #1 of 1 Archive leaderboard report
Image Super-Resolution Middlebury - 2x upscaling PASSRnet PSNR 34.05 #1 of 1 Archive leaderboard report
Image Super-Resolution Middlebury - 4x upscaling PASSRnet PSNR 28.63 #1 of 1 Archive leaderboard report
Stereo Image Super-Resolution Flickr1024 - 2x upscaling PASSRnet PSNR 28.38 #9 of 10 Archive leaderboard report
Stereo Image Super-Resolution Flickr1024 - 4x upscaling PASSRnet PSNR 23.31 #7 of 8 Archive leaderboard report
Stereo Image Super-Resolution KITTI2012 - 2x upscaling PASSRnet PSNR 30.81 #4 of 5 Archive leaderboard report
Stereo Image Super-Resolution KITTI2012 - 4x upscaling PASSRnet PSNR 26.34 #8 of 9 Archive leaderboard report
Stereo Image Super-Resolution KITTI2015 - 2x upscaling PASSRnet PSNR 30.60 #8 of 9 Archive leaderboard report
Stereo Image Super-Resolution KITTI2015 - 4x upscaling PASSRnet PSNR 26.08 #8 of 9 Archive leaderboard report
Stereo Image Super-Resolution Middlebury - 2x upscaling PASSRnet PSNR 34.23 #9 of 9 Archive leaderboard report
Stereo Image Super-Resolution Middlebury - 4x upscaling PASSRnet PSNR 28.72 #8 of 9 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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