activity
20162020
most citedLearning Graph-Level Representation for Drug Discovery

79 citations · 274 across the 15 of their papers we have counts for

collaborators

18 papers

cs.CV20205 cited

Apparel-invariant Feature Learning for Apparel-changed Person Re-identification

Zhengxu Yu, Yilun Zhao, Bin Hong +5

With the rise of deep learning methods, person Re-Identification (ReID) performance has been improved tremendously in many public datasets. However, most public ReID datasets are c…

cs.CV20203 cited

Learning to Caricature via Semantic Shape Transform

Wenqing Chu, Wei-Chih Hung, Yi-Hsuan Tsai +4

Caricature is an artistic drawing created to abstract or exaggerate facial features of a person. Rendering visually pleasing caricatures is a difficult task that requires professio…

cs.CL20191 cited

Discourse Marker Augmented Network with Reinforcement Learning for Natural Language Inference

Boyuan Pan, Yazheng Yang, Zhou Zhao +3

Natural Language Inference (NLI), also known as Recognizing Textual Entailment (RTE), is one of the most important problems in natural language processing. It requires to infer the…

cs.CV20197 cited

Localizing Unseen Activities in Video via Image Query

Zhu Zhang, Zhou Zhao, Zhijie Lin +2

Action localization in untrimmed videos is an important topic in the field of video understanding. However, existing action localization methods are restricted to a pre-defined set…

cs.CV20196 cited

COP: Customized Deep Model Compression via Regularized Correlation-Based Filter-Level Pruning

Wenxiao Wang, Cong Fu, Jishun Guo +2

Neural network compression empowers the effective yet unwieldy deep convolutional neural networks (CNN) to be deployed in resource-constrained scenarios. Most state-of-the-art appr…

cs.IR20192 cited

Query-based Interactive Recommendation by Meta-Path and Adapted Attention-GRU

Yu Zhu, Yu Gong, Qingwen Liu +6

Recently, interactive recommender systems are becoming increasingly popular. The insight is that, with the interaction between users and the system, (1) users can actively interven…