Light Field Depth Estimation

Light field depth estimation aims to reconstruct three-dimensional scene geometry from the four-dimensional light field data captured by specialized cameras. Current research heavily emphasizes addressing the challenges posed by occlusions and improving computational efficiency, often employing deep learning architectures like convolutional neural networks and transformers, along with novel cost volume construction and loss functions. These advancements lead to more accurate and robust depth maps, impacting applications such as autonomous driving, 3D modeling, and augmented/virtual reality by enabling more realistic and detailed scene understanding.