In this study, we utilized unmanned aerial vehicle (UAV) and high-precision 3D light detection and ranging (LiDAR) scanning to collect data before and after an earthquake-resistant behavior test on a reinforced concrete hybrid frame. We analyzed the deformation of the hybrid frame before and after the test and determined the specific deformation, scale, and change rule. The UAV image data was transformed into a 3D true-color model using the structure from motion (SfM) algorithm. Additionally, the 3D Delaunay surface reconstruction algorithm was used to create a 3D point cloud model and Rodriguez matrix, which are then used to align the two-phase model. Subsequently, a comparison was made in three dimensions between the distribution of the hybrid frame’s photographic and 3D point cloud models before and after undergoing earthquake-resistant behavior tests. This method allows for a precise analysis of the local deformation degree of the hybrid frame structure compared with the sensors. While the sensors can only analyze internal structural changes, this method provides results for both local and surface deformation degrees, which are not available in the sensor data. The comprehensive experimental comparison results demonstrate that the reinforced concrete hybrid frame structure had a collective rightward displacement before and after the earthquake-resistant behavior test. Moreover, nodes and edges exhibited more significant deformation, and the test resulted in a more stable overall framework.