121 citations · 358 across the 14 of their papers we have counts for
14 papers
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…
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…
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…
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…
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…
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…
Attention Driven Person Re-identification
Fan Yang, Ke Yan, Shijian Lu +3
Person re-identification (ReID) is a challenging task due to arbitrary human pose variations, background clutters, etc. It has been studied extensively in recent years, but the mul…
Trajectory Factory: Tracklet Cleaving and Re-connection by Deep Siamese Bi-GRU for Multiple Object Tracking
Cong Ma, Changshui Yang, Fan Yang +4
Multi-Object Tracking (MOT) is a challenging task in the complex scene such as surveillance and autonomous driving. In this paper, we propose a novel tracklet processing method to…
Joint Rate Allocation with Both Look-ahead And Feedback Model For High Efficiency Video Coding
Hongfei Fan, Lin Ding, Xiaodong Xie +2
The objective of joint rate allocation among multiple coded video streams is to share the bandwidth to meet the demands of minimum average distortion (minAVE) or minimum distortion…
Noise Level Estimation for Overcomplete Dictionary Learning Based on Tight Asymptotic Bounds
Rui Chen, Changshui Yang, Huizhu Jia +1
In this letter, we address the problem of estimating Gaussian noise level from the trained dictionaries in update stage. We first provide rigorous statistical analysis on the eigen…
Bayer Demosaicking Using Optimized Mean Curvature over RGB channels
Rui Chen, Huizhu Jia, Xiange Wen +1
Color artifacts of demosaicked images are often found at contours due to interpolation across edges and cross-channel aliasing. To tackle this problem, we propose a novel demosaick…
Learning a collaborative multiscale dictionary based on robust empirical mode decomposition
Rui Chen, Huizhu Jia, Xiaodong Xie +1
Dictionary learning is a challenge topic in many image processing areas. The basic goal is to learn a sparse representation from an overcomplete basis set. Due to combining the adv…
Correlation Preserving Sparse Coding Over Multi-level Dictionaries for Image Denoising
Rui Chen, Huizhu Jia, Xiaodong Xie +1
In this letter, we propose a novel image denoising method based on correlation preserving sparse coding. Because the instable and unreliable correlations among basis set can limit…
Blind restoration for non-uniform aerial images using non-local Retinex model and shearlet-based higher-order regularization
Rui Chen, Huizhu Jia, Xiaodong Xie +1
Aerial images are often degraded by space-varying motion blur and simultaneous uneven illumination. To recover high-quality aerial image from its non-uniform version, we propose a…