MACHINE LEARNING TECHNIQUES FOR SKETCH-TO-3D SHAPE GENERATION

One embodiment of the present invention sets forth a technique for performing 3D shape generation. This technique includes generating semantic features associated with an input sketch. The technique also includes generating, using a generative machine learning model, a plurality of predicted shape e...

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Bibliographische Detailangaben
Hauptverfasser: RAMPINI, Arianna, ATHERTON, Evan Patrick, LAMBOURNE, Joseph George, ASGARI TAGHANAKI, Saeid, SHAYANI, Hooman, JAYARAMAN, Pradeep Kumar, SANGHI, Aditya
Format: Patent
Sprache:eng ; fre ; ger
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Zusammenfassung:One embodiment of the present invention sets forth a technique for performing 3D shape generation. This technique includes generating semantic features associated with an input sketch. The technique also includes generating, using a generative machine learning model, a plurality of predicted shape embeddings from a set of fully masked shape embeddings based on the semantic features associated with the input sketch. The technique further includes converting the predicted shape embeddings into one or more 3D shapes. The input sketch may be a casual doodle, a professional illustration, or a 2D CAD software rendering. Each of the one or more 3D shapes may be a voxel representation, an implicit representation, or a 3D CAD software representation.