Channel Attention Based Iterative Residual Learning for Depth Map Super-Resolution
Channel Attention Based Iterative Residual Learning for Depth Map Super-Resolution
Despite the remarkable progresses made in deep learning based depth map super-resolution (DSR), how to tackle real-world degradation in low-resolution (LR) depth maps remains a major challenge. Existing DSR model is generally trained and tested on synthetic dataset, which is very different from what would get from a real depth …