Electrical Engineering and Systems Science > Image and Video Processing
arXiv:2402.02936 (eess)
[Submitted on 5 Feb 2024]
Title:Panoramic Image Inpainting With Gated Convolution And Contextual Reconstruction Loss
View a PDF of the paper titled Panoramic Image Inpainting With Gated Convolution And Contextual Reconstruction Loss, by Li Yu and 3 other authors
View PDFHTML (experimental)Abstract:Deep learning-based methods have demonstrated encouraging results in tackling the task of panoramic image inpainting. However, it is challenging for existing methods to distinguish valid pixels from invalid pixels and find suitable references for corrupted areas, thus leading to artifacts in the inpainted results. In response to these challenges, we propose a panoramic image inpainting framework that consists of a Face Generator, a Cube Generator, a side branch, and two discriminators. We use the Cubemap Projection (CMP) format as network input. The generator employs gated convolutions to distinguish valid pixels from invalid ones, while a side branch is designed utilizing contextual reconstruction (CR) loss to guide the generators to find the most suitable reference patch for inpainting the missing region. The proposed method is compared with state-of-the-art (SOTA) methods on SUN360 Street View dataset in terms of PSNR and SSIM. Experimental results and ablation study demonstrate that the proposed method outperforms SOTA both quantitatively and qualitatively.
| Comments: | Copyright 2024 IEEE - to appear in IEEE ICASSP 2024 |
| Subjects: | Image and Video Processing (eess.IV); Computer Vision and Pattern Recognition (cs.CV); Machine Learning (cs.LG); Multimedia (cs.MM) |
| Cite as: | arXiv:2402.02936 [eess.IV] |
| (orarXiv:2402.02936v1 [eess.IV] for this version) | |
| https://doi.org/10.48550/arXiv.2402.02936 arXiv-issued DOI via DataCite | |
| Journal reference: | IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2024 |
| Related DOI: | https://doi.org/10.1109/ICASSP48485.2024.10446469 DOI(s) linking to related resources |
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View a PDF of the paper titled Panoramic Image Inpainting With Gated Convolution And Contextual Reconstruction Loss, by Li Yu and 3 other authors
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