activity
20192023
most citedSESF-Fuse: An Unsupervised Deep Model for Multi-Focus Image Fusion

19 citations · 31 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2023★ 2 cited

Detector Guidance for Multi-Object Text-to-Image Generation

Luping Liu, Zijian Zhang, Yi Ren +3

Diffusion models have demonstrated impressive performance in text-to-image generation. They utilize a text encoder and cross-attention blocks to infuse textual information into ima…

cs.CV2022★ 9 cited

Unsupervised Video Domain Adaptation for Action Recognition: A Disentanglement Perspective

Pengfei Wei, Lingdong Kong, Xinghua Qu +4

Unsupervised video domain adaptation is a practical yet challenging task. In this work, for the first time, we tackle it from a disentanglement view. Our key idea is to handle the…

eess.IV2021

Data privacy protection in microscopic image analysis for material data mining

Boyuan Ma, Xiang Yin, Xiaojuan Ban +4

Recent progress in material data mining has been driven by high-capacity models trained on large datasets. However, collecting experimental data has been extremely costly owing to…

cs.CV2020★ 1 cited

End-to-End Learning for Simultaneously Generating Decision Map and Multi-Focus Image Fusion Result

Boyuan Ma, Xiang Yin, Di Wu +1

The general aim of multi-focus image fusion is to gather focused regions of different images to generate a unique all-in-focus fused image. Deep learning based methods become the m…

cs.CV2019★ 19 cited

SESF-Fuse: An Unsupervised Deep Model for Multi-Focus Image Fusion

Boyuan Ma, Xiaojuan Ban, Haiyou Huang +1

In this work, we propose a novel unsupervised deep learning model to address multi-focus image fusion problem. First, we train an encoder-decoder network in unsupervised manner to…