← Search

Jun Yi

1 accepted papers

2024

DI-MVS: Learning Efficient Multi-View Stereo With Depth-Aware Iterations

ICASSP 2024accepted

Learning-based Multi-View Stereo (MVS) methods aim to reconstruct 3D scenes from a set of 2D calibrated images. However, existing learning-based MVS methods often overlook depth maps that include the geometric shapes of the scene when constructing the cost volume. This can result in suboptimal recon…

Cited by 0SourceScholar
Jun Yi — accepted AI-conference papers · AIConfPaper