mlsanityData to 14 Oct 2026

A Multi-Layer System for Ultra-High-Resolution Static 360-Degree Telepresence

arXiv 2608.05570 ↗First posted 6 Aug 2026cs.HC cs.CVcited by 0

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Abstract (arXiv)

360-degree video telepresence offers strong immersive potential but remains constrained by the limited resolution of current capture and display hardware. Many telepresence installations feature fixed viewpoints and largely static scenes, yet optimization strategies tailored to such setups have received limited attention. We present a multi-layer, ultra-high-resolution system for static 360-degree telepresence that combines an 8K panoramic camera with a rotatable 4K pan-tilt-zoom (PTZ) camera. Our approach builds a three-layer representation: (1) a tile-based ultra-high-resolution panoramic background, generated by offline stitching high-detail 4K PTZ scans onto the base 8K panorama to achieve effective resolution beyond native capture, and represented as a set of spatial tiles; (2) a dynamic update layer that composites foreground motions from the 8K stream via real-time high-resolution background matting; and (3) a region-of-interest 4K layer that streams a real-time PTZ view of the selected region and additionally updates the corresponding background tiles over time. We evaluate the proposed system through comparisons with representative video super-resolution approaches and a user study assessing perceived detail and immersive experience. Our results indicate that tile-based background refinement, together with user-guided updates, provides a practical way to balance panoramic fidelity and interactivity in static 360-degree telepresence.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 17 of its 52 references that are in the map. First posted on arXiv 6 Aug 2026.

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17 of 52 references.

References · 17

  1. 2021LoFTR: Detector-Free Local Feature Matching with Transformerscited by 984
  2. 2021Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Datacited by 970
  3. 2023LightGlue: Local Feature Matching at Light Speedcited by 590
  4. 2020DISK: Learning local features with policy gradientcited by 312
  5. 2020Real-Time High-Resolution Background Mattingcited by 173
  6. 2021Investigating Tradeoffs in Real-World Video Super-Resolutioncited by 134
  7. 2020MODNet: Real-Time Trimap-Free Portrait Matting via Objective Decompositioncited by 127
  8. 2020Background Matting: The World is Your Green Screencited by 105
  9. 2022PanoFormer: Panorama Transformer for Indoor 360 Depth Estimationcited by 95
  10. 2023HAT: Hybrid Attention Transformer for Image Restorationcited by 66
  11. 2024DRCT: Saving Image Super-resolution away from Information Bottleneckcited by 40
  12. 2025OmniSAM: Omnidirectional Segment Anything Model for UDA in Panoramic Semantic Segmentationcited by 28
5 more
  1. 2023PanoVOS: Bridging Non-panoramic and Panoramic Views with Transformer for Video Segmentationcited by 18
  2. 2023Deep Image Matting: A Comprehensive Surveycited by 12
  3. 2024Comparative Analysis of Advanced Feature Matching Algorithms in Challenging High Spatial Resolution Optical Satellite Stereo Scenarioscited by 3
  4. 2024Resolution limit of the eye: how many pixels can we see?cited by 3
  5. 2024360U-Former: HDR Illumination Estimation with Panoramic Adapted Vision Transformerscited by 3

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