Core Insights - The article discusses the introduction of InvRGB+L, a novel inverse rendering model that integrates LiDAR intensity for reconstructing large-scale, relightable dynamic scenes from RGB+LiDAR sequences [4][26]. Group 1: Introduction of InvRGB+L - InvRGB+L is the first model to apply LiDAR intensity in inverse rendering, enhancing material estimation under varying lighting conditions [4]. - Traditional methods primarily rely on RGB inputs, often leading to inaccurate material estimates due to visible light interference [4]. Group 2: Key Innovations - The model introduces two key innovations: a physics-based LiDAR shading model and RGB-LiDAR material consistency loss, which improve the rendering results of complex scenes [4][7]. - The physics-based LiDAR shading model accurately models the relationship between LiDAR intensity values and surface material properties [7]. Group 3: Framework Components - The inverse rendering framework includes a relightable scene representation that supports decoupled and joint modeling of geometry, material, and lighting [10]. - It utilizes 3D Gaussian splats to represent scene geometry and color, incorporating physical material properties for realistic lighting interactions [13]. Group 4: Experimental Results - Quantitative results show that InvRGB+L significantly outperforms existing methods like UrbanIR in relighting tasks on the Waymo dataset, achieving a PSNR of 30.42 compared to UrbanIR's 28.84 [17][18]. - The model also demonstrates effective LiDAR intensity modeling, achieving an average intensity-RMSE of 0.063, outperforming other methods [19][20]. Group 5: Qualitative Results - Qualitative comparisons reveal that InvRGB+L effectively separates shadows from reflectance, resulting in smoother reflectance estimates compared to UrbanIR and FEGR [22]. - The model showcases versatility in scene editing, including relighting and object insertion, with seamless integration of inserted elements into the environment [23]. Group 6: Limitations and Future Work - Despite its advancements, InvRGB+L has limitations, such as potential inaccuracies in shadow rendering due to the opaque nature of Gaussian splats and insufficient handling of complex nighttime environments [26].