activity
20162022
most citedFFA-Net: Feature Fusion Attention Network for Single Image Dehazing

121 citations · 334 across the 9 of their papers we have counts for

collaborators

14 papers

cs.MM2022★ 99 cited

Towards Blind Watermarking: Combining Invertible and Non-invertible Mechanisms

Rui Ma, Mengxi Guo, Yi Hou +4

Blind watermarking provides powerful evidence for copyright protection, image authentication, and tampering identification. However, it remains a challenge to design a watermarking…

cs.LG2022

Multi-Agent Automated Machine Learning

Zhaozhi Wang, Kefan Su, Jian Zhang +4

In this paper, we propose multi-agent automated machine learning (MA2ML) with the aim to effectively handle joint optimization of modules in automated machine learning (AutoML). MA…

cs.CV2022

Enhancing and Dissecting Crowd Counting By Synthetic Data

Yi Hou, Chengyang Li, Yuheng Lu +4

In this article, we propose a simulated crowd counting dataset CrowdX, which has a large scale, accurate labeling, parameterized realization, and high fidelity. The experimental re…

cs.CV2022★ 19 cited

BBA-net: A bi-branch attention network for crowd counting

Yi Hou, Chengyang Li, Fan Yang +5

In the field of crowd counting, the current mainstream CNN-based regression methods simply extract the density information of pedestrians without finding the position of each perso…

cs.CV2019★ 121 cited

FFA-Net: Feature Fusion Attention Network for Single Image Dehazing

Xu Qin, Zhilin Wang, Yuanchao Bai +2

In this paper, we propose an end-to-end feature fusion at-tention network (FFA-Net) to directly restore the haze-free image. The FFA-Net architecture consists of three key componen…

cs.CV2019★ 95 cited

Single Image Blind Deblurring Using Multi-Scale Latent Structure Prior

Yuanchao Bai, Huizhu Jia, Ming Jiang +3

Blind image deblurring is a challenging problem in computer vision, which aims to restore both the blur kernel and the latent sharp image from only a blurry observation. Inspired b…