# Symmetric Parallax Attention for Stereo Image Super-Resolution

arXiv: https://arxiv.org/abs/2011.03802 · HTML: https://mlsanity.com/paper/2011.03802/

## Key facts

- Cited by 35 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Nov 2020.

## Built on by (most cited first, 30 of 35)

- [Refusion: Enabling Large-Size Realistic Image Restoration with Latent-Space Diffusion Models](https://mlsanity.com/paper/2304.08291/) (2023)
- [NAFSSR: Stereo Image Super-Resolution Using NAFNet](https://mlsanity.com/paper/2204.08714/) (2022)
- [Feedback Network for Mutually Boosted Stereo Image Super-Resolution and Disparity Estimation](https://mlsanity.com/paper/2106.00985/) (2021)
- [A Systematic Survey of Deep Learning-based Single-Image Super-Resolution](https://mlsanity.com/paper/2109.14335/) (2021)
- [StereoPose: Category-Level 6D Transparent Object Pose Estimation from Stereo Images via Back-View NOCS](https://mlsanity.com/paper/2211.01644/) (2022)
- [NTIRE 2022 Challenge on Stereo Image Super-Resolution: Methods and Results](https://mlsanity.com/paper/2204.09197/) (2022)
- [SwinFSR: Stereo Image Super-Resolution using SwinIR and Frequency Domain Knowledge](https://mlsanity.com/paper/2304.12556/) (2023)
- [Hybrid Transformer and CNN Attention Network for Stereo Image Super-resolution](https://mlsanity.com/paper/2305.05177/) (2023)
- [Local Motion and Contrast Priors Driven Deep Network for Infrared Small Target Super-Resolution](https://mlsanity.com/paper/2201.01014/) (2022)
- [Dense Dual-Attention Network for Light Field Image Super-Resolution](https://mlsanity.com/paper/2110.12114/) (2021)
- [NTIRE 2023 Challenge on Light Field Image Super-Resolution: Dataset, Methods and Results](https://mlsanity.com/paper/2304.10415/) (2023)
- [PFT-SSR: Parallax Fusion Transformer for Stereo Image Super-Resolution](https://mlsanity.com/paper/2303.13807/) (2023)
- [Learning Parallax Transformer Network for Stereo Image JPEG Artifacts Removal](https://mlsanity.com/paper/2207.07335/) (2022)
- [Decoupled Cross-Scale Cross-View Interaction for Stereo Image Enhancement in The Dark](https://mlsanity.com/paper/2211.00859/) (2022)
- [Cross-View Hierarchy Network for Stereo Image Super-Resolution](https://mlsanity.com/paper/2304.06236/) (2023)
- [Learning Accurate and Enriched Features for Stereo Image Super-Resolution](https://mlsanity.com/paper/2406.16001/) (2024)
- [StereoINR: Cross-View Geometry Consistent Stereo Super Resolution with Implicit Neural Representation](https://mlsanity.com/paper/2505.05509/) (2025)
- [A New Dataset and Transformer for Stereoscopic Video Super-Resolution](https://mlsanity.com/paper/2204.10039/) (2022)
- [NeuriCam: Key-Frame Video Super-Resolution and Colorization for IoT Cameras](https://mlsanity.com/paper/2207.12496/) (2022)
- [Stereo Image Rain Removal via Dual-View Mutual Attention](https://mlsanity.com/paper/2211.10104/) (2022)
- [Multi-dimension Queried and Interacting Network for Stereo Image Deraining](https://mlsanity.com/paper/2309.10319/) (2023)
- [Toward Real World Stereo Image Super-Resolution via Hybrid Degradation Model and Discriminator for Implied Stereo Image Information](https://mlsanity.com/paper/2312.07934/) (2023)
- [Multi-Level Feature Fusion Network for Lightweight Stereo Image Super-Resolution](https://mlsanity.com/paper/2405.05497/) (2024)
- [Neural Stereo Video Compression with Hybrid Disparity Compensation](https://mlsanity.com/paper/2504.20383/) (2025)
- [ShipSRDet: An End-to-End Remote Sensing Ship Detector Using Super-Resolved Feature Representation](https://mlsanity.com/paper/2103.09699/) (2021)
- [DIffSteISR: Harnessing Diffusion Prior for Superior Real-world Stereo Image Super-Resolution](https://mlsanity.com/paper/2408.07516/) (2024)
- [SNNSIR: A Simple Spiking Neural Network for Stereo Image Restoration](https://mlsanity.com/paper/2508.12271/) (2025)
- [Deep Learning Empowered Super-Resolution: A Comprehensive Survey and Future Prospects](https://mlsanity.com/paper/2509.22692/) (2025)
- [SEGSRNet for Stereo-Endoscopic Image Super-Resolution and Surgical Instrument Segmentation](https://mlsanity.com/paper/2404.13330/) (2024)
- [NAFRSSR: a Lightweight Recursive Network for Efficient Stereo Image Super-Resolution](https://mlsanity.com/paper/2405.08423/) (2024)

## Abstract (arXiv)

Although recent years have witnessed the great advances in stereo image super-resolution (SR), the beneficial information provided by binocular systems has not been fully used. Since stereo images are highly symmetric under epipolar constraint, in this paper, we improve the performance of stereo image SR by exploiting symmetry cues in stereo image pairs. Specifically, we propose a symmetric bi-directional parallax attention module (biPAM) and an inline occlusion handling scheme to effectively interact cross-view information. Then, we design a Siamese network equipped with a biPAM to super-resolve both sides of views in a highly symmetric manner. Finally, we design several illuminance-robust losses to enhance stereo consistency. Experiments on four public datasets demonstrate the superior performance of our method. Source code is available at https://github.com/YingqianWang/iPASSR.