We present a novel high-resolution complex field extraction technique utilizing the U-Net-based architecture to effectively overcome the inherent resolution limitations of polarization camera with micro-polarized array. Our method extracts high-resolution complex field information, achieving a resolution comparable to that of the original polarization camera. Enabling the parallel phase-shifting digital holography technique, we extracted high-resolution complex field information from four high-resolution phase-shifted interference patterns predicted by our network directly at the hologram plane. Being independent of numerical propagation in dataset acquisition, our network reconstructs objects at various depths without DC and conjugate noise. By training the network with real-valued interference patterns and using only a single pair of low- and high-resolution input and ground truth interference patterns, we simplify computational complexity and improve efficiency. Our simulations demonstrate the network's robustness to variations in random phase distributions and transverse shifts in the input patterns. Validation results show that images have been successfully reconstructed with improved quality and enhanced spatial resolution.