Hierarchical Similarity Loss Enhanced Depth and Structural Fidelity in Monocular RGB-to-Depth Mapping with Adversarial Training
The conversion of monocular RGB images to depth maps is crucial in robotic applications. Current supervised learning approaches, dependent on high-quality RGB-Depth pairs, struggle with indoor environments characterized by multiple objects and fluctuating lighting, leading to inaccurate and unstable…