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We present a deep neural framework that allows users to create surfaces from a stream of sparse 3D sketch strokes.
Our network consists of a global surface estimation module followed by a local surface refinement.
This facilitates in the incremental prediction of surfaces.
Thus, our proposed method works with 3D sketch strokes and estimate a surface interactively in real time.
We compare the proposed method with various state-of-the-art methods and show its efficacy for surface fitting.
Further, we integrate our method into an existing Blender based 3D content creation pipeline to show its usefulness in 3D modeling.
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