Quick, Draw!

By Allison Lai. 2020

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

I Lead, You Help but Only with Enough Details: Understanding User Experience of Co-Creation with Artificial Intelligence (2018, background): “[24] is an online game that challenges players to draw a picture of an Although these new interfaces and algorithms are still in the experimental stages, they have opened up the possibility for humans and AI to work together to produce creative outcomes.”
DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation (2020, background): “Existing vector graphics datasets either only contain straight lines [22] or are constrained to font generation [11].”
Universal Representation Learning from Multiple Domains for Few-shot Classification (2021, background): “We also see that our method outperforms two strong baselines, Best SDL and MDL in all datasets except in QuickDraw.”
Meta Learning on a Sequence of Imbalanced Domains with Difficulty Awareness (2021, unknown): “…etc. Proposed benchmark To simulate realistic imbalanced domain sequences, we construct a new benchmark and collect 6 domains with varying degree of similarity and difficulty, including Quickdraw [29], AIRCRAFT [40], CUB [62], Miniimagenet [57], Omniglot [35], Necessities from Logo-2K+ [60].”