SketchINR: A First Look into Sketches as Implicit Neural Representations

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

We propose SketchINR, to advance the representation of vector sketches with implicit neural models. A variable length vector sketch is compressed into a latent space of fixed dimension that implicitly encodes the underlying shape as a function of time and strokes. The learned function predicts the xy point coordinates in a sketch at each time and stroke. Despite its simplicity, SketchINR outperforms existing representations at multiple tasks: (i) Encoding an entire sketch dataset into a fixed size latent vector, SketchINR gives 60× and 10× data compression over raster and vector sketches, respectively. (ii) SketchINR’s auto-decoder provides a much higher-fidelity representation than other learned vector sketch representations, and is uniquely able to scale to complex vector sketches such as FS-COCO. (iii) SketchINR supports parallelisation that can decode/render ∼100× faster than other learned vector representations such as SketchRNN. (iv) SketchINR, for the first time, emulates the human ability to reproduce a sketch with varying abstraction in terms of number and complexity of strokes. As a first look at implicit sketches, SketchINR’s compact high-fidelity representation will support future work in modelling long and complex sketches.
Original languageEnglish
Title of host publication2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
PublisherIEEE
Number of pages10
Publication statusAccepted/In press - 27 Feb 2024
EventThe IEEE/CVF Conference on Computer Vision and Pattern Recognition 2024 - Seattle, United States
Duration: 17 Jun 202421 Jun 2024
https://cvpr.thecvf.com/

Publication series

NameProceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition.)
PublisherIEEE
ISSN (Print)1063-6919
ISSN (Electronic)2575-7075

Conference

ConferenceThe IEEE/CVF Conference on Computer Vision and Pattern Recognition 2024
Abbreviated titleCVPR 2024
Country/TerritoryUnited States
CitySeattle
Period17/06/2421/06/24
Internet address

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