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Found 6 papers, 6 papers with code
Wassersplines for Neural Vector Field--Controlled Animation
Trajectories are then computed by advecting keyframes through the velocity field.
DeepCurrents: Learning Implicit Representations of Shapes with Boundaries
Recent techniques have been successful in reconstructing surfaces as level sets of learned functions (such as signed distance fields) parameterized by deep neural networks.
Polygonal Building Extraction by Frame Field Learning
While state of the art image segmentation models typically output segmentations in raster format, applications in geographic information systems often require vector polygons.
MarioNette: Self-Supervised Sprite Learning
Artists and video game designers often construct 2D animations using libraries of sprites -- textured patches of objects and characters.
Polygonal Building Segmentation by Frame Field Learning
While state of the art image segmentation models typically output segmentations in raster format, applications in geographic information systems often require vector polygons.
Deep Parametric Shape Predictions using Distance Fields
Many tasks in graphics and vision demand machinery for converting shapes into consistent representations with sparse sets of parameters; these representations facilitate rendering, editing, and storage.
