Toward Semantic Communication for Real-time Mobile 3D Reconstruction
Real-time mobile 3D reconstruction is fundamental to many emerging applications such as autonomous navigation and digital twin construction, where a moving platform continuously captures an image stream and transmit to a computing server for scene understanding. Unlike offline reconstruction, camera poses and scene geometry are estimated on-the-fly during acquisition, making multi-view consistency a real-time requirement and rendering geometric estimation highly sensitive to communication-induced distortions. Semantic communication (SemCom) transmits compact semantic information, offering a pr
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Paper → model → repo connections mined from source citations (Tier-1 exact match).
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- PossiblePossibly related (embedding) · 53%Lingbot-map: A 3D foundation model for reconstructing scenes from streaming data →
- PossiblePossibly related (embedding) · 47%Showcase: geolocating a dashcam video without GPS, only from the footage [P] →
- FuzzyOverlapping authors or contributors · 62%google-research/google-research →
“Shared author/contributor keys: sun”
- FuzzyOverlapping authors or contributors · 62%modular/modular →
“Shared author/contributor keys: liu”
- FuzzyOverlapping authors or contributors · 62%thedotmack/claude-mem →
“Shared author/contributor keys: kai”
- FuzzyOverlapping authors or contributors · 62%DietrichGebert/ponytail →
“Shared author/contributor keys: cheng”
- FuzzySimilar title/name (fuzzy) · 59%microsoft/semantic-kernel →
“Fuzzy title match (0.73): “Toward Semantic Communication for Real-time Mobile 3D Recons” ≈ “microsoft/semantic-kernel””
- LinkedLinked via arxiv author · 85%Fangzhou Zhao →
“Toward Semantic Communication for Real-time Mobile 3D Reconstruction”