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DrawMon: A Distributed System for Detection of Atypical Sketch Content in Concurrent Pictionary Games

Authors: Bansal, Nikhil; Kartik Gupta; Kiruthika Kannan; Sivani Pentapati; Sarvadevabhatla, Ravi Kiran;

DrawMon: A Distributed System for Detection of Atypical Sketch Content in Concurrent Pictionary Games

Abstract

Dataset for training CanvasNet, a model for detecting atypical sketch instances. CanvasNet processes the rendered image as input and outputs a list of atypical activities (if any) along with associated meta-information (atypical content category, 2-D spatial location). For more details, visit our page https://drawm0n.github.io/.

Keywords

computer-vision deep-learning dataset sketch-recognition pictionary text-detection-recognition tensorflow2 separable-convolution acmmm2022

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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