DTGS: Physics-Embedded Dynamic Thermal 3D Reconstruction with Gaussian Splatting

Dynamic scene representation and rendering in the visible spectrum has been extensively studied. Compared to visible-light imaging, thermal infrared sensing offers all-weather observation and strong penetration capability, enabling perception in low-visibility environments. However, dynamic reconstruction in thermal infrared scenes is challenged due to atmospheric transport effects and interference from low-emissivity background regions, which often leads to motion blur and details loss in rendered results. To address these issues, we propose DTGS, a physics-driven dynamic 3D scene reconstruction approach. DTGS factorizes dynamic thermal scenes into radiometric and geometric components, modeling radiometric changes via rendering that integrates atmospheric radiative transfer, while capturing geometric deformations through Adaptive Temporal Gaussian basis. In addition, we design a thermal-radiance-weighted structural similarity loss to suppress gradient interference from low-radiance noisy regions. Furthermore, to demonstrate the effectiveness of our method, a large-scale dataset for this field named Dynamic_LTR is created. Experimental results demonstrate that our method achieves a 2.7 dB improvement in PSNR, a twofold speedup in rendering, and a threefold reduction in training time. The code and datasets will be available after acceptance.