Viewport-based Neural 360° Image Compression
Given the popularity of 360° images on social media platforms, 360° image compression becomes a critical technology for media storage and transmission. Conventional 360° image compression pipeline projects the spherical image into a single 2D plane, leading to issues of oversampling and distortion. In this paper, we propose a novel viewport-based neural compression pipeline for 360° images. By replacing the image projection in conventional 360° image compression pipelines with viewport extraction and efficiently compressing multiple viewports, the proposed pipeline minimizes the inherent oversampling and distortion issues. However, viewport extraction impedes information sharing between m...
| Authors | Jingwei Liao, Bo Chen, Klara Nahrstedt et al. |
|---|---|
| Primary category | eess.IV |
| Published | 24 March 2026 |
| Last updated at source | 24 March 2026 |
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