首页|NeRFCom: Feature Transform Coding Meets Neural Radiance Field for Free-View 3-D Scene Semantic Transmission

NeRFCom: Feature Transform Coding Meets Neural Radiance Field for Free-View 3-D Scene Semantic Transmission

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  • NETL
  • NSTL
  • IEEE
We introduce NeRFCom, a novel communication system designed for end-to-end 3D scene transmission. Compared to traditional systems relying on handcrafted NeRF semantic feature decomposition for compression and well-adaptive channel coding for transmission error correction, our NeRFCom employs a nonlinear transform and learned probabilistic models, enabling flexible variable-rate joint source-channel coding and efficient bandwidth allocation aligned with the NeRF semantic feature’s different contribution to the 3D scene synthesis fidelity. Experimental results demonstrate that NeRFCom achieves free-view 3D scene efficient transmission while maintaining robustness under adverse channel conditions.

Three-dimensional displaysNeural radiance fieldSymbolsFeature extractionDecodingEntropyOptimizationImage reconstructionEncodingTransforms

Weijie Yue、Zhongwei Si、Bolin Wu、Sixian Wang、Xiaoqi Qin、Kai Niu、Jincheng Dai、Ping Zhang

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Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China

State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China

2025

10.1109/LCOMM.2025.3544882

IEEE communications letters

IEEE communications letters

ISSN：
年,卷(期)：2025.29(5)
  • 17