The prediction of superconducting transition temperatures ( ) from electronic band structures remains challenging due to the complex interplay of electronic correlations, lattice dynamics, and symmetry. Here, we develop DeeperBand, a symmetry-aware 3D Vision Transformer model, to decode band structure features linked to superconductivity. By integrating density functional theory calibrated bands with an attention mechanism, DeeperBand identifies steep Fermi-level density-of-states slopes and flat bands as key indicators, aligning with Bardeen, Cooper, and Schrieffer and van Hove singularity paradigms. Trained on 2474 samples with symmetry-informed augmentation (1362 superconductors