453 citations · 1.5k across the 44 of their papers we have counts for
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cs.CV2016★ 45 cited
Stacked Generative Adversarial Networks
Xun Huang, Yixuan Li, Omid Poursaeed +2
In this paper, we propose a novel generative model named Stacked Generative Adversarial Networks (SGAN), which is trained to invert the hierarchical representations of a bottom-up…
cs.CV2016★ 62 cited
A Powerful Generative Model Using Random Weights for the Deep Image Representation
Kun He, Yan Wang, John Hopcroft
To what extent is the success of deep visualization due to the training? Could we do deep visualization using untrained, random weight networks? To address this issue, we explore n…
cs.SI2016★ 33 cited
In a World That Counts: Clustering and Detecting Fake Social Engagement at Scale
Yixuan Li, Oscar Martinez, Xing Chen +2
How can web services that depend on user generated content discern fake social engagement activities by spammers from legitimate ones? In this paper, we focus on the social site of…