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Found 2 papers, 1 papers with code
NeUDF: Leaning Neural Unsigned Distance Fields with Volume Rendering
Multi-view shape reconstruction has achieved impressive progresses thanks to the latest advances in neural implicit surface rendering.
NeAT: Learning Neural Implicit Surfaces with Arbitrary Topologies from Multi-view Images
In particular, NeAT represents the 3D surface as a level set of a signed distance function (SDF) with a validity branch for estimating the surface existence probability at the query positions.
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