Web: http://arxiv.org/abs/2203.01703

Sept. 19, 2022, 1:13 a.m. | Dominik J. E. Waibel, Scott Atwell, Matthias Meier, Carsten Marr, Bastian Rieck

stat.ML updates on arXiv.org arxiv.org

Reconstructing 3D objects from 2D images is both challenging for our brains
and machine learning algorithms. To support this spatial reasoning task,
contextual information about the overall shape of an object is critical.
However, such information is not captured by established loss terms (e.g. Dice
loss). We propose to complement geometrical shape information by including
multi-scale topological features, such as connected components, cycles, and
voids, in the reconstruction loss. Our method uses cubical complexes to
calculate topological features of 3D …

3d reconstruction arxiv information loss scale terms

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