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ThermalGate-GS: Frequency-Gated Graph Splatting for Thermal Novel View Synthesis

  • Yaoxing Wang
  • , Wenkang Chen
  • , Yuheng Li
  • , Guangqian Guo
  • , Chaowei Wang
  • , Yan Di
  • , Dongsheng Yang
  • , Kai Zhang
  • , Shan Gao
  • Northwestern Polytechnical University Xian
  • National Key Laboratory of Unmanned Aerial Vehicle Technology
  • Shenzhen University

科研成果: 期刊稿件文章同行评审

摘要

Thermal infrared imaging is pivotal for all-weather 3D perception, yet analyzing thermal information remains a formidable challenge due to the complexity of heat conduction. Unlike visible light, heat conduction acts as a natural low-pass filter that suppresses high-frequency textural details, causing severe geometric ambiguities and “ghosting” artifacts in standard 3D reconstruction pipelines. To accurately model the inherently diffusive thermal field for high-fidelity reconstruction, we propose Frequency-Gated Graph Splatting (ThermalGate-GS), a frame work that explicitly decouples the scene into diffusive thermal distributions (low-frequency) and sharp structural boundaries (high-frequency). Within this framework, we introduce a novel Frequency-Gated Anisotropic Diffusion mechanism. Specifically, the frequency-gating module utilizes extracted high-frequency structural cues to determine spatially-adaptive gating weights. Subsequently, these weights drive an anisotropic diffusion process that dynamically regulates thermal feature propagation, pro moting smoothness on object surfaces while suppressing cross-boundary bleeding. Finally, these spectrally refined features are employed to regress 3D Gaussian attributes, substantially alleviating the ambiguity in thermal reconstruction. Extensive experiments demonstrate that ThermalGate-GS achieves state-of-the-art performance, with a notable 7.94 dB PSNR improvement on the ThermoScenes benchmark over prior physics-inspired baselines.

源语言英语
期刊IEEE Transactions on Image Processing
DOI
出版状态已接受/待刊 - 2026

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