EpiS improves generalizable neural surface reconstruction from sparse views by guiding epipolar feature aggregation with cost volumes, using an epipolar transformer, and applying pretrained monocular depth constraints, outperforming prior methods on DTU and BlendedMVS.
IEEE TRANS- ACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE32(8) (2010) 3
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Neural Surface Reconstruction from Sparse Views Using Epipolar Geometry
EpiS improves generalizable neural surface reconstruction from sparse views by guiding epipolar feature aggregation with cost volumes, using an epipolar transformer, and applying pretrained monocular depth constraints, outperforming prior methods on DTU and BlendedMVS.