In this paper, we present a dual Single Pixel Camera (SPC) operating in the Short Wave InfraRed (SWIR) spectral range that reconstructs high resolution images from an ensemble of compressed measurements. The SWIR spectrum provides significant benefits in many applications due to its night vision capabilities and its ability to penetrate smoke and fog. Walsh-Hadamard matrices are used for generating pseudo-random measurements which speed up the reconstruction and enable reconstruction of high resolution images. Total variation regularization is used for finding a sparse solution in the gradient space. The detectors have been fitted with analog filters and amplification in order to capture scenes in low light. A number of outdoor scenes with varying illumination have been collected using the dual single pixel sensor. Visual inspection of the reconstructed SWIR images indicate that most scenes and objects can be identified with a lower subsampling ratio (SR) compared to a single detector setup. The image quality is consistently better than with one detector, with similar results achieved with fewer samples or better results with the same number of samples. We also present measurements on moving objects in the scene and movements in the SPC unit and compare the results between single and dual detectors.