Learning Based Multi View Stereo

Learning-based multi-view stereo (MVS) aims to reconstruct high-fidelity 3D models from multiple 2D images by leveraging deep learning techniques. Current research emphasizes improving accuracy and completeness, particularly in challenging scenarios like textureless regions and large depth variations, through advancements in model architectures such as transformers, ray-based methods, and novel cost volume aggregation strategies. These improvements are significant for applications requiring precise 3D scene understanding, including augmented/virtual reality, autonomous driving, and robotics.