activity
20122023
most citedDisentangling Semantic-to-visual Confusion for Zero-shot Learning

30 citations · 82 across the 13 of their papers we have counts for

collaborators

22 papers

cs.LG2023

Graph Neural Networks with Diverse Spectral Filtering

Jingwei Guo, Kaizhu Huang, Xinping Yi +1

Spectral Graph Neural Networks (GNNs) have achieved tremendous success in graph machine learning, with polynomial filters applied for graph convolutions, where all nodes share the…

cs.CL20232 cited

Learning by Analogy: Diverse Questions Generation in Math Word Problem

Zihao Zhou, Maizhen Ning, Qiufeng Wang +4

Solving math word problem (MWP) with AI techniques has recently made great progress with the success of deep neural networks (DNN), but it is far from being solved. We argue that t…

cs.CV20228 cited

Rethinking Data Augmentation for Single-source Domain Generalization in Medical Image Segmentation

Zixian Su, Kai Yao, Xi Yang +3

Single-source domain generalization (SDG) in medical image segmentation is a challenging yet essential task as domain shifts are quite common among clinical image datasets. Previou…

cs.CV2022

SSD: Towards Better Text-Image Consistency Metric in Text-to-Image Generation

Zhaorui Tan, Xi Yang, Zihan Ye +4

Generating consistent and high-quality images from given texts is essential for visual-language understanding. Although impressive results have been achieved in generating high-qua…

cs.CV20221 cited

A Survey of Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and Methodologies

Zhuang Qian, Kaizhu Huang, Qiu-Feng Wang +1

In the last a few decades, deep neural networks have achieved remarkable success in machine learning, computer vision, and pattern recognition. Recent studies however show that neu…

cs.CV2021

Each Attribute Matters: Contrastive Attention for Sentence-based Image Editing

Liuqing Zhao, Fan Lyu, Fuyuan Hu +3

Sentence-based Image Editing (SIE) aims to deploy natural language to edit an image. Offering potentials to reduce expensive manual editing, SIE has attracted much interest recentl…