most citedMulti-label Zero-shot Classification by Learning to Transfer from External Knowledge

2 citations · 2 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2020

Addressing Class Imbalance in Scene Graph Parsing by Learning to Contrast and Score

He Huang, Shunta Saito, Yuta Kikuchi +3

Scene graph parsing aims to detect objects in an image scene and recognize their relations. Recent approaches have achieved high average scores on some popular benchmarks, but fail…

cs.CV20202 cited

Multi-label Zero-shot Classification by Learning to Transfer from External Knowledge

He Huang, Yuanwei Chen, Wei Tang +4

Multi-label zero-shot classification aims to predict multiple unseen class labels for an input image. It is more challenging than its single-label counterpart. On one hand, the unc…

cs.CV2018

Generative Dual Adversarial Network for Generalized Zero-shot Learning

He Huang, Changhu Wang, Philip S. Yu +1

This paper studies the problem of generalized zero-shot learning which requires the model to train on image-label pairs from some seen classes and test on the task of classifying n…

cs.HC2018

dpMood: Exploiting Local and Periodic Typing Dynamics for Personalized Mood Prediction

He Huang, Bokai Cao, Philip S. Yu +2

Mood disorders are common and associated with significant morbidity and mortality. Early diagnosis has the potential to greatly alleviate the burden of mental illness and the ever…

cs.CV2018

An Introduction to Image Synthesis with Generative Adversarial Nets

He Huang, Philip S. Yu, Changhu Wang

There has been a drastic growth of research in Generative Adversarial Nets (GANs) in the past few years. Proposed in 2014, GAN has been applied to various applications such as comp…