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Cascade Cost Volume For High-Resolution Multi-View Stereo and Stereo Matching by Arunabh Sharma is a document available to read on EtoBox.
The paper introduces a novel cascade cost volume formulation for high-resolution multi-view stereo and stereo matching, aimed at improving memory and time efficiency. By utilizing a feature pyramid and adaptive depth sampling, the proposed method significantly enhances reconstruction accuracy while reducing GPU memory usage and run-time. The approach demonstrates state-of-the-art performance on benchmark datasets, outperforming existing methods in both accuracy and efficiency.
- Author
- Arunabh Sharma
- Language
- EN