activity
20192024
most citedDM-GAN: Dynamic Memory Generative Adversarial Networks for Text-to-Image Synthesis

45 citations · 55 across the 6 of their papers we have counts for

collaborators

8 papers

cs.HC20243 cited

CultiVerse: Towards Cross-Cultural Understanding for Paintings with Large Language Model

Wei Zhang, Wong Kam-Kwai, Biying Xu +5

The integration of new technology with cultural studies enhances our understanding of cultural heritage but often struggles to connect with diverse audiences. It is challenging to…

cs.CV20221 cited

Interactive Image Synthesis with Panoptic Layout Generation

Bo Wang, Tao Wu, Minfeng Zhu +1

Interactive image synthesis from user-guided input is a challenging task when users wish to control the scene structure of a generated image with ease.Although remarkable progress…

cs.LG20205 cited

SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations

Hao-Zhe Feng, Kezhi Kong, Minghao Chen +3

Semi-supervised variational autoencoders (VAEs) have obtained strong results, but have also encountered the challenge that good ELBO values do not always imply accurate inference r…

cs.LG2020

KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation

Hao-Zhe Feng, Zhaoyang You, Minghao Chen +5

Conventional unsupervised multi-source domain adaptation (UMDA) methods assume all source domains can be accessed directly. This neglects the privacy-preserving policy, that is, al…

cs.GR2020

Exemplar-based Layout Fine-tuning for Node-link Diagrams

Jiacheng Pan, Wei Chen, Xiaodong Zhao +6

We design and evaluate a novel layout fine-tuning technique for node-link diagrams that facilitates exemplar-based adjustment of a group of substructures in batching mode. The key…

cs.SI20201 cited

DRGraph: An Efficient Graph Layout Algorithm for Large-scale Graphs by Dimensionality Reduction

Minfeng Zhu, Wei Chen, Yuanzhe Hu +3

Efficient layout of large-scale graphs remains a challenging problem: the force-directed and dimensionality reduction-based methods suffer from high overhead for graph distance and…