270 citations · 878 across the 64 of their papers we have counts for
24 papers · 1 filter
Unsupervised Alternating Optimization for Blind Hyperspectral Imagery Super-resolution
Jiangtao Nie, Lei Zhang, Wei Wei +2
Despite the great success of deep model on Hyperspectral imagery (HSI) super-resolution(SR) for simulated data, most of them function unsatisfactory when applied to the real data,…
Meta-Generating Deep Attentive Metric for Few-shot Classification
Lei Zhang, Fei Zhou, Wei Wei +1
Learning to generate a task-aware base learner proves a promising direction to deal with few-shot learning (FSL) problem. Existing methods mainly focus on generating an embedding m…
Learning Image-adaptive 3D Lookup Tables for High Performance Photo Enhancement in Real-time
Hui Zeng, Jianrui Cai, Lida Li +2
Recent years have witnessed the increasing popularity of learning based methods to enhance the color and tone of photos. However, many existing photo enhancement methods either del…
Tasks Integrated Networks: Joint Detection and Retrieval for Image Search
Lei Zhang, Zhenwei He, Yi Yang +2
The traditional object retrieval task aims to learn a discriminative feature representation with intra-similarity and inter-dissimilarity, which supposes that the objects in an ima…
Progressive Semantic-Aware Style Transformation for Blind Face Restoration
Chaofeng Chen, Xiaoming Li, Lingbo Yang +3
Face restoration is important in face image processing, and has been widely studied in recent years. However, previous works often fail to generate plausible high quality (HQ) resu…
Domain Private and Agnostic Feature for Modality Adaptive Face Recognition
Yingguo Xu, Lei Zhang, Qingyan Duan
Heterogeneous face recognition is a challenging task due to the large modality discrepancy and insufficient cross-modal samples. Most existing works focus on discriminative feature…
Hard Negative Samples Emphasis Tracker without Anchors
Zhongzhou Zhang, Lei Zhang
Trackers based on Siamese network have shown tremendous success, because of their balance between accuracy and speed. Nevertheless, with tracking scenarios becoming more and more s…
Hierarchical Bi-Directional Feature Perception Network for Person Re-Identification
Zhipu Liu, Lei Zhang, Yang Yang
Previous Person Re-Identification (Re-ID) models aim to focus on the most discriminative region of an image, while its performance may be compromised when that region is missing ca…
Blind Face Restoration via Deep Multi-scale Component Dictionaries
Xiaoming Li, Chaofeng Chen, Shangchen Zhou +3
Recent reference-based face restoration methods have received considerable attention due to their great capability in recovering high-frequency details on real low-quality images.…
Plug-and-Play Image Restoration with Deep Denoiser Prior
Kai Zhang, Yawei Li, Wangmeng Zuo +3
Recent works on plug-and-play image restoration have shown that a denoiser can implicitly serve as the image prior for model-based methods to solve many inverse problems. Such a pr…
SMAP: A Joint Dimensionality Reduction Scheme for Secure Multi-Party Visualization
Jiazhi Xia, Tianxiang Chen, Lei Zhang +5
Nowadays, as data becomes increasingly complex and distributed, data analyses often involve several related datasets that are stored on different servers and probably owned by diff…
Suppress and Balance: A Simple Gated Network for Salient Object Detection
Xiaoqi Zhao, Youwei Pang, Lihe Zhang +2
Most salient object detection approaches use U-Net or feature pyramid networks (FPN) as their basic structures. These methods ignore two key problems when the encoder exchanges inf…
Label Propagation with Augmented Anchors: A Simple Semi-Supervised Learning baseline for Unsupervised Domain Adaptation
Yabin Zhang, Bin Deng, Kui Jia +1
Motivated by the problem relatedness between unsupervised domain adaptation (UDA) and semi-supervised learning (SSL), many state-of-the-art UDA methods adopt SSL principles (e.g.,…
Dual Adversarial Network: Toward Real-world Noise Removal and Noise Generation
Zongsheng Yue, Qian Zhao, Lei Zhang +1
Real-world image noise removal is a long-standing yet very challenging task in computer vision. The success of deep neural network in denoising stimulates the research of noise gen…
Weakness Analysis of Cyberspace Configuration Based on Reinforcement Learning
Lei Zhang, Wei Bai, Shize Guo +3
In this work, we present a learning-based approach to analysis cyberspace configuration. Unlike prior methods, our approach has the ability to learn from past experience and improv…
Aligning Partially Overlapping Point Sets: an Inner Approximation Algorithm
Wei Lian, WangMeng Zuo, Lei Zhang
Aligning partially overlapping point sets where there is no prior information about the value of the transformation is a challenging problem in computer vision. To achieve this goa…
Branch-Cooperative OSNet for Person Re-Identification
Lei Zhang, Xiaofu Wu, Suofei Zhang +1
Multi-branch is extensively studied for learning rich feature representation for person re-identification (Re-ID). In this paper, we propose a branch-cooperative architecture over…
Novel Human-Object Interaction Detection via Adversarial Domain Generalization
Yuhang Song, Wenbo Li, Lei Zhang +6
We study in this paper the problem of novel human-object interaction (HOI) detection, aiming at improving the generalization ability of the model to unseen scenarios. The challenge…
GraftNet: An Engineering Implementation of CNN for Fine-grained Multi-label Task
Chunhua Jia, Lei Zhang, Hui Huang +3
Multi-label networks with branches are proved to perform well in both accuracy and speed, but lacks flexibility in providing dynamic extension onto new labels due to the low effici…
Blockchain-enabled Resource Management and Sharing for 6G Communications
Hao Xu, Paulo Valente Klaine, Oluwakayode Onireti +3
The sixth generation (6G) network must provide performance superior to previous generations in order to meet the requirements of emerging services and applications, such as multi-g…
Gradient Centralization: A New Optimization Technique for Deep Neural Networks
Hongwei Yong, Jianqiang Huang, Xiansheng Hua +1
Optimization techniques are of great importance to effectively and efficiently train a deep neural network (DNN). It has been shown that using the first and second order statistics…
Probability Weighted Compact Feature for Domain Adaptive Retrieval
Fuxiang Huang, Lei Zhang, Yang Yang +1
Domain adaptive image retrieval includes single-domain retrieval and cross-domain retrieval. Most of the existing image retrieval methods only focus on single-domain retrieval, whi…
Interference and Rate Analysis of Multinumerology NOMA
Stephen McWade, Mark F. Flanagan, Lei Zhang +1
5G communication systems and beyond are envisioned to support an extremely diverse set of use cases with different performance requirements. These different requirements necessitat…
Continual Local Replacement for Few-shot Learning
Canyu Le, Zhonggui Chen, Xihan Wei +2
The goal of few-shot learning is to learn a model that can recognize novel classes based on one or few training data. It is challenging mainly due to two aspects: (1) it lacks good…