Skip to main content

PFT-SSR: Parallax Fusion Transformer for Stereo Image Super-Resolution

Hansheng GUO (The Chinese University of Hong Kong); Juncheng Li (The Chinese University of Hong Kong); Guangwei Gao (Nanjing University of Posts and Telecommunications); Zhi Li (East China Normal University); Tieyong Zeng (The Chinese University of Hong Kong)

  • SPS
    Members: Free
    IEEE Members: $11.00
    Non-members: $15.00
06 Jun 2023

Stereo image super-resolution aims to boost the performance of image super-resolution by exploiting the supplementary information provided by binocular systems. Although previous methods have achieved promising results, they did not fully utilize the information of cross-view and intra-view. To further unleash the potential of binocular images, in this letter, we propose a novel Transformer-based parallax fusion module called Parallax Fusion Transformer (PFT). PFT employs a Cross-view Fusion Transformer (CVFT) to utilize cross-view information and an Intra-view Refinement Transformer (IVRT) for intra-view feature refinement. Meanwhile, we adopted the Swin Transformer as the backbone for feature extraction and SR reconstruction to form a pure Transformer architecture called PFT-SSR. Extensive experiments and ablation studies show that PFT-SSR achieves competitive results and outperforms most SOTA methods. Source code is available at https://github.com/MIVRC/PFT-PyTorch.

More Like This

  • SPS
    Members: Free
    IEEE Members: $11.00
    Non-members: $15.00
  • SPS
    Members: Free
    IEEE Members: $11.00
    Non-members: $15.00
  • SPS
    Members: Free
    IEEE Members: $11.00
    Non-members: $15.00