DriveFace: A Cross-Spectral Through-Glass Face Dataset for On-the-Move Vehicular Border Control

The continuous growth in cross-border mobility places increasing pressure on existing border control infrastructures, motivating on-the-move biometric authentication, in which travellers are identified directly inside their vehicles at checkpoints. Face recognition is well-suited to this setting, as it can be acquired passively and at a distance. Its development, however, is hindered by the lack of representative datasets: existing benchmarks are collected in controlled environments and do not capture the challenges inherent to vehicular acquisition, including motion blur, variable illumination, occlusions, and cross-spectral enrollment. To address this gap, we introduce DriveFace, a dataset for on-the-move face recognition in border-control scenarios, comprising NIR vehicle-crossing videos paired with smartphone-based pre-enrollment data. Baseline evaluations with state-of-the-art models show clear performance limitations under these realistic conditions, highlighting the need for dedicated methods to advance the field.

Highlights:

• 70 consenting subjects captured over two sessions approximately two months apart, pairing visible-spectrum smartphone pre-enrollment with in-vehicle NIR probes.
• Cross-spectral, through-glass acquisition: RGB references matched against NIR probes captured through automotive windows at varying tint and viewing angles, under stationary and moving conditions.
• DriveFace-PAD presentation-attack subset with print, replay, and mask attacks under multiple tint and illumination levels.
• Rich metadata (tint level, illumination, head pose, vehicle speed) and standardized FR and PAD protocols with strong baseline results.

Paper
arXiv
Project page
Code
Dataset

Latex citation:

@inproceedings{george2026driveface,
  title={DriveFace: A Cross-Spectral Through-Glass Face Dataset for On-the-Move Vehicular Border Control},
  author={George, Anjith and Luevano, Luis S and Komaty, Alain and Al Amine, Zeina and Vidit, Vidit and Marcel, S\'ebastien},
  booktitle={2026 IEEE International Joint Conference on Biometrics (IJCB)},
  year={2026},
}