activity
20152021
most citedLearning Hypergraph-regularized Attribute Predictors

16 citations · 36 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV20216 cited

Dizygotic Conditional Variational AutoEncoder for Multi-Modal and Partial Modality Absent Few-Shot Learning

Yi Zhang, Sheng Huang, Xi Peng +1

Data augmentation is a powerful technique for improving the performance of the few-shot classification task. It generates more samples as supplements, and then this task can be tra…

cs.SE20211 cited

Plot2API: Recommending Graphic API from Plot via Semantic Parsing Guided Neural Network

Zeyu Wang, Sheng Huang, Zhongxin Liu +4

Plot-based Graphic API recommendation (Plot2API) is an unstudied but meaningful issue, which has several important applications in the context of software engineering and data visu…

cs.CV202013 cited

Deep Semantic Dictionary Learning for Multi-label Image Classification

Fengtao Zhou, Sheng Huang, Yun Xing

Compared with single-label image classification, multi-label image classification is more practical and challenging. Some recent studies attempted to leverage the semantic informat…

cs.CV2016

Regression-based Hypergraph Learning for Image Clustering and Classification

Sheng Huang, Dan Yang, Bo Liu +1

Inspired by the recently remarkable successes of Sparse Representation (SR), Collaborative Representation (CR) and sparse graph, we present a novel hypergraph model named Regressio…

cs.CV201516 cited

Learning Hypergraph-regularized Attribute Predictors

Sheng Huang, Mohamed Elhoseiny, Ahmed Elgammal +1

We present a novel attribute learning framework named Hypergraph-based Attribute Predictor (HAP). In HAP, a hypergraph is leveraged to depict the attribute relations in the data. T…