114 citations · 373 across the 27 of their papers we have counts for
27 papers
Diffusion Model Based Visual Compensation Guidance and Visual Difference Analysis for No-Reference Image Quality Assessment
Zhaoyang Wang, Bo Hu, Mingyang Zhang +4
Existing free-energy guided No-Reference Image Quality Assessment (NR-IQA) methods still suffer from finding a balance between learning feature information at the pixel level of th…
A Dual Domain Multi-exposure Image Fusion Network based on the Spatial-Frequency Integration
Guang Yang, Jie Li, Xinbo Gao
Multi-exposure image fusion aims to generate a single high-dynamic image by integrating images with different exposures. Existing deep learning-based multi-exposure image fusion me…
Multi-Scene Generalized Trajectory Global Graph Solver with Composite Nodes for Multiple Object Tracking
Yan Gao, Haojun Xu, Nannan Wang +2
The global multi-object tracking (MOT) system can consider interaction, occlusion, and other ``visual blur'' scenarios to ensure effective object tracking in long videos. Among the…
A Multi-scale Information Integration Framework for Infrared and Visible Image Fusion
Guang Yang, Jie Li, Hanxiao Lei +1
Infrared and visible image fusion aims at generating a fused image containing the intensity and detail information of source images, and the key issue is effectively measuring and…
EtC: Temporal Boundary Expand then Clarify for Weakly Supervised Video Grounding with Multimodal Large Language Model
Guozhang Li, Xinpeng Ding, De Cheng +3
Early weakly supervised video grounding (WSVG) methods often struggle with incomplete boundary detection due to the absence of temporal boundary annotations. To bridge the gap betw…
Image-specific Convolutional Kernel Modulation for Single Image Super-resolution
Yuanfei Huang, Jie Li, Yanting Hu +2
Recently, deep-learning-based super-resolution methods have achieved excellent performances, but mainly focus on training a single generalized deep network by feeding numerous samp…
Stimuli-Aware Visual Emotion Analysis
Jingyuan Yang, Jie Li, Xiumei Wang +2
Visual emotion analysis (VEA) has attracted great attention recently, due to the increasing tendency of expressing and understanding emotions through images on social networks. Dif…
A Circular-Structured Representation for Visual Emotion Distribution Learning
Jingyuan Yang, Jie Li, Leida Li +2
Visual Emotion Analysis (VEA) has attracted increasing attention recently with the prevalence of sharing images on social networks. Since human emotions are ambiguous and subjectiv…
Drafting and Revision: Laplacian Pyramid Network for Fast High-Quality Artistic Style Transfer
Tianwei Lin, Zhuoqi Ma, Fu Li +6
Artistic style transfer aims at migrating the style from an example image to a content image. Currently, optimization-based methods have achieved great stylization quality, but exp…
Transitional Learning: Exploring the Transition States of Degradation for Blind Super-resolution
Yuanfei Huang, Jie Li, Yanting Hu +2
Being extremely dependent on iterative estimation of the degradation prior or optimization of the model from scratch, the existing blind super-resolution (SR) methods are generally…
Multi-Margin based Decorrelation Learning for Heterogeneous Face Recognition
Bing Cao, Nannan Wang, Xinbo Gao +2
Heterogeneous face recognition (HFR) refers to matching face images acquired from different domains with wide applications in security scenarios. This paper presents a deep neural…
Facial Attribute Capsules for Noise Face Super Resolution
Jingwei Xin, Nannan Wang, Xinrui Jiang +3
Existing face super-resolution (SR) methods mainly assume the input image to be noise-free. Their performance degrades drastically when applied to real-world scenarios where the in…
Video Face Super-Resolution with Motion-Adaptive Feedback Cell
Jingwei Xin, Nannan Wang, Jie Li +2
Video super-resolution (VSR) methods have recently achieved a remarkable success due to the development of deep convolutional neural networks (CNN). Current state-of-the-art CNN me…
Image Fine-grained Inpainting
Zheng Hui, Jie Li, Xiumei Wang +1
Image inpainting techniques have shown promising improvement with the assistance of generative adversarial networks (GANs) recently. However, most of them often suffered from compl…
AIM 2019 Challenge on Real-World Image Super-Resolution: Methods and Results
Andreas Lugmayr, Martin Danelljan, Radu Timofte +18
This paper reviews the AIM 2019 challenge on real world super-resolution. It focuses on the participating methods and final results. The challenge addresses the real world setting,…
Progressive Perception-Oriented Network for Single Image Super-Resolution
Zheng Hui, Jie Li, Xinbo Gao +1
Recently, it has been demonstrated that deep neural networks can significantly improve the performance of single image super-resolution (SISR). Numerous studies have concentrated o…
A sparse annotation strategy based on attention-guided active learning for 3D medical image segmentation
Zhenxi Zhang, Jie Li, Zhusi Zhong +2
3D image segmentation is one of the most important and ubiquitous problems in medical image processing. It provides detailed quantitative analysis for accurate disease diagnosis, a…
Reconstructing Perceived Images from Brain Activity by Visually-guided Cognitive Representation and Adversarial Learning
Ziqi Ren, Jie Li, Xuetong Xue +4
Reconstructing visual stimulus (image) only from human brain activity measured with functional Magnetic Resonance Imaging (fMRI) is a significant and meaningful task in Human-AI co…
An Attention-Guided Deep Regression Model for Landmark Detection in Cephalograms
Zhusi Zhong, Jie Li, Zhenxi Zhang +2
Cephalometric tracing method is usually used in orthodontic diagnosis and treatment planning. In this paper, we propose a deep learning based framework to automatically detect anat…
Shared Predictive Cross-Modal Deep Quantization
Erkun Yang, Cheng Deng, Chao Li +3
With explosive growth of data volume and ever-increasing diversity of data modalities, cross-modal similarity search, which conducts nearest neighbor search across different modali…
Channel-wise and Spatial Feature Modulation Network for Single Image Super-Resolution
Yanting Hu, Jie Li, Yuanfei Huang +1
The performance of single image super-resolution has achieved significant improvement by utilizing deep convolutional neural networks (CNNs). The features in deep CNN contain diffe…
Single Image Super-Resolution via Cascaded Multi-Scale Cross Network
Yanting Hu, Xinbo Gao, Jie Li +2
The deep convolutional neural networks have achieved significant improvements in accuracy and speed for single image super-resolution. However, as the depth of network grows, the i…
Restricting Greed in Training of Generative Adversarial Network
Haoxuan You, Zhicheng Jiao, Haojun Xu +3
Generative adversarial network (GAN) has gotten wide re-search interest in the field of deep learning. Variations of GAN have achieved competitive results on specific tasks. Howeve…
Random Sampling for Fast Face Sketch Synthesis
Nannan Wang, Xinbo Gao, Jie Li
Exemplar-based face sketch synthesis plays an important role in both digital entertainment and law enforcement. It generally consists of two parts: neighbor selection and reconstru…