1k citations · 1.7k across the 17 of their papers we have counts for
18 papers
Multi-Modal Object Re-Identification with Prompt-S6 and Semantic-Aware Knowledge Guidance
Weixiang Zhou, Jiabei Zuo, Yuhao Wang +3
Multi-modal object Re-Identification (ReID) aims to retrieve specific objects by integrating complementary information from multiple modalities. However, existing multi-modal ReID…
Learning A Coarse-to-Fine Diffusion Transformer for Image Restoration
Liyan Wang, Qinyu Yang, Cong Wang +3
Recent years have witnessed the remarkable performance of diffusion models in various vision tasks. However, for image restoration that aims to recover clear images with sharper de…
A New Simple Stochastic Gradient Descent Type Algorithm With Lower Computational Complexity for Bilevel Optimization
Haimei Huo, Risheng Liu, Zhixun Su
Bilevel optimization has been widely used in many machine learning applications such as hyperparameter optimization and meta learning. Recently, many simple stochastic gradient des…
Real-World Denoising via Diffusion Model
Cheng Yang, Lijing Liang, Zhixun Su
Real-world image denoising is an extremely important image processing problem, which aims to recover clean images from noisy images captured in natural environments. In recent year…
Joint Self-Attention and Scale-Aggregation for Self-Calibrated Deraining Network
Cong Wang, Yutong Wu, Zhixun Su +1
In the field of multimedia, single image deraining is a basic pre-processing work, which can greatly improve the visual effect of subsequent high-level tasks in rainy conditions. I…
DCSFN: Deep Cross-scale Fusion Network for Single Image Rain Removal
Cong Wang, Xiaoying Xing, Zhixun Su +1
Rain removal is an important but challenging computer vision task as rain streaks can severely degrade the visibility of images that may make other visions or multimedia tasks fail…
Physical Model Guided Deep Image Deraining
Honghe Zhu, Cong Wang, Yajie Zhang +2
Single image deraining is an urgent task because the degraded rainy image makes many computer vision systems fail to work, such as video surveillance and autonomous driving. So, de…
Non-rigid 3D shape retrieval based on multi-view metric learning
Haohao Li, Shengfa Wang, Nannan Li +2
This study presents a novel multi-view metric learning algorithm, which aims to improve 3D non-rigid shape retrieval. With the development of non-rigid 3D shape analysis, there exi…
Learning Video-Story Composition via Recurrent Neural Network
Guangyu Zhong, Yi-Hsuan Tsai, Sifei Liu +2
In this paper, we propose a learning-based method to compose a video-story from a group of video clips that describe an activity or experience. We learn the coherence between video…
Deep Blind Image Inpainting
Yang Liu, Jinshan Pan, Zhixun Su
Image inpainting is a challenging problem as it needs to fill the information of the corrupted regions. Most of the existing inpainting algorithms assume that the positions of the…
An Optimization Framework with Flexible Inexact Inner Iterations for Nonconvex and Nonsmooth Programming
Yiyang Wang, Risheng Liu, Xiaoliang Song +1
In recent years, numerous vision and learning tasks have been (re)formulated as nonconvex and nonsmooth programmings(NNPs). Although some algorithms have been proposed for particul…
Sparse Coding and Counting for Robust Visual Tracking
Risheng Liu, Jing Wang, Yiyang Wang +2
In this paper, we propose a novel sparse coding and counting method under Bayesian framwork for visual tracking. In contrast to existing methods, the proposed method employs the co…
Parallel matrix factorization for low-rank tensor completion
Yangyang Xu, Ruru Hao, Wotao Yin +1
Higher-order low-rank tensors naturally arise in many applications including hyperspectral data recovery, video inpainting, seismic data recon- struction, and so on. We propose a n…
Kernel Estimation from Salient Structure for Robust Motion Deblurring
Jinshan Pan, Risheng Liu, Zhixun Su +1
Blind image deblurring algorithms have been improving steadily in the past years. Most state-of-the-art algorithms, however, still cannot perform perfectly in challenging cases, es…
Fixed-Rank Representation for Unsupervised Visual Learning
Risheng Liu, Zhouchen Lin, Fernando De la Torre +1
Subspace clustering and feature extraction are two of the most commonly used unsupervised learning techniques in computer vision and pattern recognition. State-of-the-art technique…
Toward Designing Intelligent PDEs for Computer Vision: An Optimal Control Approach
Risheng Liu, Zhouchen Lin, Wei Zhang +2
Many computer vision and image processing problems can be posed as solving partial differential equations (PDEs). However, designing PDE system usually requires high mathematical s…
Linearized Alternating Direction Method with Adaptive Penalty for Low-Rank Representation
Zhouchen Lin, Risheng Liu, Zhixun Su
Low-rank representation (LRR) is an effective method for subspace clustering and has found wide applications in computer vision and machine learning. The existing LRR solver is bas…
Solving Principal Component Pursuit in Linear Time via Filtering
Risheng Liu, Zhouchen Lin, Siming Wei +1
In the past decades, exactly recovering the intrinsic data structure from corrupted observations, which is known as robust principal component analysis (RPCA), has attracted tremen…