Elevating Visual Experiences: Advanced Networks for Video Super-Resolution

The rapid expansion of video-based applications has intensified the demand for high-quality visual content. Video super-resolution (VSR) stands at the forefront of this evolution. VSR includes spatial super-resolution (enhancing the resolution of each frame), temporal super-resolution (video frame interpolation), and spatio-temporal super-resolution, which combines both.

VSR is transforming fields such as satellite imaging, surveillance, medical imaging, ultra-high-definition streaming, and augmented/virtual reality. Despite recent progress, significant open problems hinder the deployment of robust, high-fidelity VSR systems in real-world scenarios.

This Research Topic seeks innovative, neural network-based solutions that push the boundaries of VSR by addressing its most pressing challenges.

We encourage submissions on novel theoretical and practical advancements in VSR, particularly those tackling unresolved challenges, including but not limited to

• Robust motion handling and temporal consistency

• Self-supervised and unsupervised VSR

• Real-world degradation and blind VSR

• Efficiency and real-time processing

• Perceptual quality and artifact suppression

• Scalability and generalization

• Hybrid approaches combining traditional video processing with deep learning

• Applications and case studies

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Data Report
• Editorial
• FAIR² Data
• Hypothesis and Theory
• Methods
• Mini Review
• Original Research
• Perspective
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Data Report
• Editorial
• FAIR² Data
• Hypothesis and Theory
• Methods
• Mini Review
• Original Research
• Perspective
• Review

Keywords: Video Super-Resolution, VSR, Neural Networks, Temporal Consistency, Real-World Degradation, Real-Time Processing

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.