Deep Learning-Based Depth Estimation from Light Field

  • Date in the past
  • Tuesday, 23. July 2024, 13:00
  • Mathematikon B, room B128
    • Titus Leistner
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    Mathematikon B
    Room B128

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Deep Learning-Based Depth Estimation from Light Fields

Light fields enable precise and robust depth estimation. With the shift from consumer light field cameras, new applications now require high-resolution, wide-baseline camera arrays and reliable confidence measures. This thesis introduces EPI-Shift, a deep-learning framework effective for both small- and wide-baseline light fields, and three deep learning methods for multimodal posterior regression. These methods extend the applicability to wide-baseline light fields and enhance posterior regression, performing on par with state-of-the-art approaches.