SketchINR: A First Look into Sketches as Implicit Neural Representations

Timothy Hospedales, Tao Xiang, Yi-Zhe Song, Aneeshan Sain, Ayan Kumar Bhunia, Hmrishav Bandyopadhyay, Pinaki Nath Chowdhury

arXiv · PDF · Open in the Atlas

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Abstract

Storage (Bytes) Figure 1. SketchINR is an implicit neural representation for sequential vector sketches. It is the first neural representation with sufficient fidelity to be a drop-in replacement for the raw sketch data (a). The representation is significantly higher fidelity than existing learned representations such as SketchRNN [28], especially for more complex sketches (b, left). SketchINR also provides state-of-the-art sketch compression, with a substantially more compact representation than either vector or raster sketches (b, right).

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