## Qualitative Image Comparison Chart: Aerial Scene Reconstruction Methods ### Overview The image presents a side-by-side comparison of five different 3D reconstruction methods applied to aerial imagery, with a ground truth (GT) reference. Three rows show different scenes: a solar farm, an urban building complex, and a street-level view. Each method is evaluated using colored bounding boxes (red for errors/artifacts, green for accurate regions) to highlight reconstruction quality. ### Components/Axes - **X-axis**: Five reconstruction methods: 1. 3D-GS 2. Scaffold-GS 3. City-GS 4. Hierarchical-GS 5. Our-Scaffold-GS - **Y-axis**: Three scene categories: 1. Solar farm (top row) 2. Urban building complex (middle row) 3. Street-level view (bottom row) - **Legend**: - Red boxes: Artifacts/errors - Green boxes: Accurate regions - Yellow box: Ground truth (GT) reference ### Detailed Analysis #### Scene 1: Solar Farm - **3D-GS**: Red box highlights misaligned solar panel rows. - **Scaffold-GS**: Red box shows missing panel sections. - **City-GS**: Red box indicates distorted panel geometry. - **Hierarchical-GS**: Red box marks panel misalignment; green box shows improved accuracy. - **Our-Scaffold-GS**: Green box covers entire panel array; minimal red artifacts. - **GT**: Yellow box confirms correct panel layout. #### Scene 2: Urban Building Complex - **3D-GS**: Red box highlights distorted building edges. - **Scaffold-GS**: Red box shows missing roof details. - **City-GS**: Red box indicates vegetation misclassification. - **Hierarchical-GS**: Red box marks roof edge artifacts; green box shows improved building structure. - **Our-Scaffold-GS**: Green box covers entire building complex; red box only on minor roof details. - **GT**: Yellow box confirms accurate building geometry. #### Scene 3: Street-Level View - **3D-GS**: Red box highlights road surface artifacts. - **Scaffold-GS**: Red box shows missing vehicle details. - **City-GS**: Red box indicates tree canopy distortion. - **Hierarchical-GS**: Red box marks road edge artifacts; green box shows improved vehicle rendering. - **Our-Scaffold-GS**: Green box covers entire street view; red box only on minor vehicle details. - **GT**: Yellow box confirms accurate street-level details. ### Key Observations 1. **Our-Scaffold-GS** consistently shows fewer red boxes (errors) and more green boxes (accurate regions) across all scenes compared to other methods. 2. **Hierarchical-GS** demonstrates partial improvements over baseline methods but still exhibits significant artifacts. 3. **3D-GS** and **Scaffold-GS** show the most severe reconstruction errors, particularly in complex geometries (solar panels, building edges). 4. **GT** serves as the ideal reference, with all methods failing to fully match its accuracy, though Our-Scaffold-GS comes closest. ### Interpretation The data suggests that the proposed **Our-Scaffold-GS** method significantly improves 3D reconstruction quality by: - Reducing geometric distortions in complex structures (solar panels, building facades) - Better preserving small-scale details (vehicles, vegetation) - Maintaining accuracy in both large-scale (urban layouts) and small-scale (street-level) scenes Notable trends include: - Methods using hierarchical processing (Hierarchical-GS) show incremental improvements over non-hierarchical approaches - The scaffold-based approach (Our-Scaffold-GS) outperforms traditional 3D-GS and Scaffold-GS by addressing panel/building alignment issues - All methods struggle with texture preservation in vegetated areas, as evidenced by persistent red boxes in green spaces This comparison highlights the importance of scaffold-based processing and hierarchical refinement in achieving near-ground-truth reconstruction quality for aerial imagery.