Search Results for author: Yanning Zhang

Found 56 papers, 8 papers with code

Learnable Locality-Sensitive Hashing for Video Anomaly Detection

1 code implementation15 Nov 2021 Yue Lu, Congqi Cao, Yanning Zhang

In this paper, we propose a novel distance-based VAD method to take advantage of all the available normal data efficiently and flexibly.

Abnormal Event Detection In Video

NAS-FCOS: Efficient Search for Object Detection Architectures

1 code implementation24 Oct 2021 Ning Wang, Yang Gao, Hao Chen, Peng Wang, Zhi Tian, Chunhua Shen, Yanning Zhang

Neural Architecture Search (NAS) has shown great potential in effectively reducing manual effort in network design by automatically discovering optimal architectures.

Neural Architecture Search Object Detection

Text-based Person Search in Full Images via Semantic-Driven Proposal Generation

no code implementations27 Sep 2021 Shizhou Zhang, Duo Long, Yitao Gao, Liying Gao, Qian Zhang, Kai Niu, Yanning Zhang

Finding target persons in full scene images with a query of text description has important practical applications in intelligent video surveillance. However, different from the real-world scenarios where the bounding boxes are not available, existing text-based person retrieval methods mainly focus on the cross modal matching between the query text descriptions and the gallery of cropped pedestrian images.

Pedestrian Detection Person Retrieval +3

Unsupervised Cross-Modal Distillation for Thermal Infrared Tracking

1 code implementation31 Jul 2021 Jingxian Sun, Lichao Zhang, Yufei zha, Abel Gonzalez-Garcia, Peng Zhang, Wei Huang, Yanning Zhang

To solve this problem, we propose to distill representations of the TIR modality from the RGB modality with Cross-Modal Distillation (CMD) on a large amount of unlabeled paired RGB-TIR data.

Transfer Learning

Unsupervised Video Summarization with a Convolutional Attentive Adversarial Network

no code implementations24 May 2021 Guoqiang Liang, Yanbing Lv, Shucheng Li, Shizhou Zhang, Yanning Zhang

Specifically, the generator employs a fully convolutional sequence network to extract global representation of a video, and an attention-based network to output normalized importance scores.

Unsupervised Video Summarization

Center Prediction Loss for Re-identification

no code implementations30 Apr 2021 Lu Yang, Yunlong Wang, Lingqiao Liu, Peng Wang, Lu Chi, Zehuan Yuan, Changhu Wang, Yanning Zhang

In this paper, we propose a new loss based on center predictivity, that is, a sample must be positioned in a location of the feature space such that from it we can roughly predict the location of the center of same-class samples.

Dynamic Image Restoration and Fusion Based on Dynamic Degradation

no code implementations26 Apr 2021 Aiqing Fang, Xinbo Zhao, Jiaqi Yang, Yanning Zhang

In addition, a dynamic degradation kernel is proposed to improve the robustness of image restoration and fusion.

Image Restoration

Efficient Spatialtemporal Context Modeling for Action Recognition

no code implementations20 Mar 2021 Congqi Cao, Yue Lu, Yifan Zhang, Dongmei Jiang, Yanning Zhang

Inspired from 2D criss-cross attention used in segmentation task, we propose a recurrent 3D criss-cross attention (RCCA-3D) module to model the dense long-range spatiotemporal contextual information in video for action recognition.

Action Recognition

Pluggable Weakly-Supervised Cross-View Learning for Accurate Vehicle Re-Identification

no code implementations9 Mar 2021 Lu Yang, Hongbang Liu, Jinghao Zhou, Lingqiao Liu, Lei Zhang, Peng Wang, Yanning Zhang

Learning cross-view consistent feature representation is the key for accurate vehicle Re-identification (ReID), since the visual appearance of vehicles changes significantly under different viewpoints.

Vehicle Re-Identification

Learning Depth via Leveraging Semantics: Self-supervised Monocular Depth Estimation with Both Implicit and Explicit Semantic Guidance

no code implementations11 Feb 2021 Rui Li, Xiantuo He, Danna Xue, Shaolin Su, Qing Mao, Yu Zhu, Jinqiu Sun, Yanning Zhang

While the mappings between image and pixel-wise depth are well-studied in current methods, the correlation between image, depth and scene semantics, however, is less considered.

Monocular Depth Estimation

Non-uniform Motion Deblurring with Blurry Component Divided Guidance

no code implementations15 Jan 2021 Pei Wang, Wei Sun, Qingsen Yan, Axi Niu, Rui Li, Yu Zhu, Jinqiu Sun, Yanning Zhang

To tackle the above problems, we present a deep two-branch network to deal with blurry images via a component divided module, which divides an image into two components based on the representation of blurry degree.

Blind Image Deblurring Image Deblurring +1

Semantic-Guided Representation Enhancement for Self-supervised Monocular Trained Depth Estimation

no code implementations15 Dec 2020 Rui Li, Qing Mao, Pei Wang, Xiantuo He, Yu Zhu, Jinqiu Sun, Yanning Zhang

Based on this framework, we enhance the local feature representation by sampling and feeding the point-based features that locate on the semantic edges to an individual Semantic-guided Edge Enhancement module (SEEM), which is specifically designed for promoting depth estimation on the challenging semantic borders.

Depth Estimation Semantic Segmentation

Meta-Generating Deep Attentive Metric for Few-shot Classification

no code implementations3 Dec 2020 Lei Zhang, Fei Zhou, Wei Wei, Yanning Zhang

To mitigate this problem, we present a novel deep metric meta-generation method that turns to an orthogonal direction, ie, learning to adaptively generate a specific metric for a new FSL task based on the task description (eg, a few labelled samples).

Classification Few-Shot Learning +1

Unsupervised Alternating Optimization for Blind Hyperspectral Imagery Super-resolution

no code implementations3 Dec 2020 Jiangtao Nie, Lei Zhang, Wei Wei, Zhiqiang Lang, Yanning Zhang

One of the main reason comes from the fact that the predefined degeneration models (e. g. blur in spatial domain) utilized by most HSI SR methods often exist great discrepancy with the real one, which results in these deep models overfit and ultimately degrade their performance on real data.

Meta-Learning Super-Resolution

On Efficient and Robust Metrics for RANSAC Hypotheses and 3D Rigid Registration

no code implementations10 Nov 2020 Jiaqi Yang, Zhiqiang Huang, Siwen Quan, Qian Zhang, Yanning Zhang, Zhiguo Cao

This paper focuses on developing efficient and robust evaluation metrics for RANSAC hypotheses to achieve accurate 3D rigid registration.

Few-shot Action Recognition with Implicit Temporal Alignment and Pair Similarity Optimization

no code implementations13 Oct 2020 Congqi Cao, Yajuan Li, Qinyi Lv, Peng Wang, Yanning Zhang

Few-shot learning aims to recognize instances from novel classes with few labeled samples, which has great value in research and application.

Action Recognition Few-Shot Learning +1

AE-Netv2: Optimization of Image Fusion Efficiency and Network Architecture

no code implementations5 Oct 2020 Aiqing Fang, Xinbo Zhao, Jiaqi Yang, Beibei Qin, Yanning Zhang

Finally, we explore the commonness and characteristics of different image fusion tasks, which provides a research basis for further research on the continuous learning characteristics of human brain in the field of image fusion.

AE-Net: Autonomous Evolution Image Fusion Method Inspired by Human Cognitive Mechanism

no code implementations17 Jul 2020 Aiqing Fang, Xinbo Zhao, Jiaqi Yang, Shihao Cao, Yanning Zhang

Firstly, the relationship between human brain cognitive mechanism and image fusion task is analyzed and a physical model is established to simulate human brain cognitive mechanism.

IllumiNet: Transferring Illumination from Planar Surfaces to Virtual Objects in Augmented Reality

no code implementations12 Jul 2020 Di Xu, Zhen Li, Yanning Zhang, Qi Cao

This paper presents an illumination estimation method for virtual objects in real environment by learning.

A Robust Attentional Framework for License Plate Recognition in the Wild

no code implementations6 Jun 2020 Linjiang Zhang, Peng Wang, Hui Li, Zhen Li, Chunhua Shen, Yanning Zhang

On the other hand, the 2D attentional based license plate recognizer with an Xception-based CNN encoder is capable of recognizing license plates with different patterns under various scenarios accurately and robustly.

Image Generation License Plate Recognition

Attention-based network for low-light image enhancement

no code implementations20 May 2020 Cheng Zhang, Qingsen Yan, Yu Zhu, Xianjun Li, Jinqiu Sun, Yanning Zhang

Extensive experiments demonstrate the superiority of the proposed network in terms of suppressing the chromatic aberration and noise artifacts in enhancement, especially when the low-light image has severe noise.

Denoising Low-Light Image Enhancement

Learning to Compare Relation: Semantic Alignment for Few-Shot Learning

no code implementations29 Feb 2020 Congqi Cao, Yanning Zhang

First, we introduce a semantic alignment loss to align the relation statistics of the features from samples that belong to the same category.

Few-Shot Learning Metric Learning

Learning to Zoom-in via Learning to Zoom-out: Real-world Super-resolution by Generating and Adapting Degradation

no code implementations8 Jan 2020 Dong Gong, Wei Sun, Qinfeng Shi, Anton Van Den Hengel, Yanning Zhang

Most learning-based super-resolution (SR) methods aim to recover high-resolution (HR) image from a given low-resolution (LR) image via learning on LR-HR image pairs.

Super-Resolution

Cross-Modal Image Fusion Theory Guided by Subjective Visual Attention

no code implementations23 Dec 2019 Aiqing Fang, Xinbo Zhao, Yanning Zhang

In order to improve the robustness and contextual awareness of image fusion tasks, we proposed a multi-task auxiliary learning image fusion theory guided by subjective attention.

Auxiliary Learning

A Cross-Modal Image Fusion Method Guided by Human Visual Characteristics

no code implementations18 Dec 2019 Aiqing Fang, Xinbo Zhao, Jiaqi Yang, Yanning Zhang

The characteristics of feature selection, nonlinear combination and multi-task auxiliary learning mechanism of the human visual perception system play an important role in real-world scenarios, but the research of image fusion theory based on the characteristics of human visual perception is less.

Auxiliary Learning Feature Selection

Person Re-identification in Aerial Imagery

1 code implementation14 Aug 2019 Shizhou Zhang, Qi Zhang, Yifei Yang, Xing Wei, Peng Wang, Bingliang Jiao, Yanning Zhang

Our method can learn a discriminative and compact feature representation for ReID in aerial imagery and can be trained in an end-to-end fashion efficiently.

Object Detection Person Re-Identification

A Performance Evaluation of Correspondence Grouping Methods for 3D Rigid Data Matching

no code implementations5 Jul 2019 Jiaqi Yang, Ke Xian, Peng Wang, Yanning Zhang

Seeking consistent point-to-point correspondences between 3D rigid data (point clouds, meshes, or depth maps) is a fundamental problem in 3D computer vision.

3D Object Recognition Point Cloud Registration

Evaluating Local Geometric Feature Representations for 3D Rigid Data Matching

no code implementations29 Jun 2019 Jiaqi Yang, Siwen Quan, Peng Wang, Yanning Zhang

The outcomes present interesting findings that may shed new light on this community and provide complementary perspectives to existing evaluations on the topic of local geometric feature description.

Object Recognition Point Cloud Registration

Attention-guided Network for Ghost-free High Dynamic Range Imaging

4 code implementations CVPR 2019 Qingsen Yan, Dong Gong, Qinfeng Shi, Anton Van Den Hengel, Chunhua Shen, Ian Reid, Yanning Zhang

Ghosting artifacts caused by moving objects or misalignments is a key challenge in high dynamic range (HDR) imaging for dynamic scenes.

Optical Flow Estimation

Vehicle Re-identification in Aerial Imagery: Dataset and Approach

no code implementations ICCV 2019 Peng Wang, Bingliang Jiao, Lu Yang, Yifei Yang, Shizhou Zhang, Wei Wei, Yanning Zhang

It is capable of explicitly detecting discriminative parts for each specific vehicle and significantly outperforms the evaluated baselines and state-of-the-art vehicle ReID approaches.

Vehicle Re-Identification

Pixel-aware Deep Function-mixture Network for Spectral Super-Resolution

no code implementations24 Mar 2019 Lei Zhang, Zhiqiang Lang, Peng Wang, Wei Wei, Shengcai Liao, Ling Shao, Yanning Zhang

To address this problem, we propose a pixel-aware deep function-mixture network for SSR, which is composed of a new class of modules, termed function-mixture (FM) blocks.

Super-Resolution

MPTV: Matching Pursuit Based Total Variation Minimization for Image Deconvolution

no code implementations12 Oct 2018 Dong Gong, Mingkui Tan, Qinfeng Shi, Anton Van Den Hengel, Yanning Zhang

Compared to existing methods, MPTV is less sensitive to the choice of the trade-off parameter between data fitting and regularization.

Image Deconvolution

A Pulmonary Nodule Detection Model Based on Progressive Resolution and Hierarchical Saliency

no code implementations2 Jul 2018 Jun-Jie Zhang, Yong Xia, Yanning Zhang

Detection of pulmonary nodules on chest CT is an essential step in the early diagnosis of lung cancer, which is critical for best patient care.

Accurate Spectral Super-resolution from Single RGB Image Using Multi-scale CNN

no code implementations10 Jun 2018 Yiqi Yan, Lei Zhang, Jun Li, Wei Wei, Yanning Zhang

Different from traditional hyperspectral super-resolution approaches that focus on improving the spatial resolution, spectral super-resolution aims at producing a high-resolution hyperspectral image from the RGB observation with super-resolution in spectral domain.

Super-Resolution

Adaptive Importance Learning for Improving Lightweight Image Super-resolution Network

no code implementations5 Jun 2018 Lei Zhang, Peng Wang, Chunhua Shen, Lingqiao Liu, Wei Wei, Yanning Zhang, Anton Van Den Hengel

In this study, we revisit this problem from an orthog- onal view, and propose a novel learning strategy to maxi- mize the pixel-wise fitting capacity of a given lightweight network architecture.

Image Super-Resolution

Learning Deep Gradient Descent Optimization for Image Deconvolution

1 code implementation10 Apr 2018 Dong Gong, Zhen Zhang, Qinfeng Shi, Anton Van Den Hengel, Chunhua Shen, Yanning Zhang

Extensive experiments on synthetic benchmarks and challenging real-world images demonstrate that the proposed deep optimization method is effective and robust to produce favorable results as well as practical for real-world image deblurring applications.

Blind Image Deblurring Image Deblurring +1

Significantly Fast and Robust Fuzzy C-MeansClustering Algorithm Based on MorphologicalReconstruction and Membership Filtering

no code implementations IEEE 2018 Tao Lei, Xiaohong Jia, Yanning Zhang, Lifeng He, Hongy-ing Meng, Senior Member, and Asoke K. Nandi, Fellow, IEEE

However, the introduction oflocal spatial information often leads to a high computationalcomplexity, arising out of an iterative calculation of the distancebetween pixels within local spatial neighbors and clusteringcenters.

Semantic Segmentation

Self-Paced Kernel Estimation for Robust Blind Image Deblurring

no code implementations ICCV 2017 Dong Gong, Mingkui Tan, Yanning Zhang, Anton Van Den Hengel, Qinfeng Shi

Rather than attempt to identify outliers to the model a priori, we instead propose to sequentially identify inliers, and gradually incorporate them into the estimation process.

Blind Image Deblurring Image Deblurring

Beyond Low Rank: A Data-Adaptive Tensor Completion Method

no code implementations3 Aug 2017 Lei Zhang, Wei Wei, Qinfeng Shi, Chunhua Shen, Anton Van Den Hengel, Yanning Zhang

The prior for the non-low-rank structure is established based on a mixture of Gaussians which is shown to be flexible enough, and powerful enough, to inform the completion process for a variety of real tensor data.

From Motion Blur to Motion Flow: a Deep Learning Solution for Removing Heterogeneous Motion Blur

no code implementations CVPR 2017 Dong Gong, Jie Yang, Lingqiao Liu, Yanning Zhang, Ian Reid, Chunhua Shen, Anton Van Den Hengel, Qinfeng Shi

The critical observation underpinning our approach is thus that learning the motion flow instead allows the model to focus on the cause of the blur, irrespective of the image content.

Tensor Power Iteration for Multi-Graph Matching

no code implementations CVPR 2016 Xinchu Shi, Haibin Ling, Weiming Hu, Junliang Xing, Yanning Zhang

Due to its wide range of applications, matching between two graphs has been extensively studied and remains an active topic.

Graph Matching

Blind Image Deconvolution by Automatic Gradient Activation

no code implementations CVPR 2016 Dong Gong, Mingkui Tan, Yanning Zhang, Anton Van Den Hengel, Qinfeng Shi

We show here that a subset of the image gradients are adequate to estimate the blur kernel robustly, no matter the gradient image is sparse or not.

Image Deconvolution

Hyperspectral Compressive Sensing Using Manifold-Structured Sparsity Prior

no code implementations ICCV 2015 Lei Zhang, Wei Wei, Yanning Zhang, Fei Li, Chunhua Shen, Qinfeng Shi

To reconstruct hyperspectral image (HSI) accurately from a few noisy compressive measurements, we present a novel manifold-structured sparsity prior based hyperspectral compressive sensing (HCS) method in this study.

Compressive Sensing

Reweighted Laplace Prior Based Hyperspectral Compressive Sensing for Unknown Sparsity

no code implementations CVPR 2015 Lei Zhang, Wei Wei, Yanning Zhang, Chunna Tian, Fei Li

To address this problem, a novel reweighted Laplace prior based hyperspectral compressive sensing method is proposed in this study.

Compressive Sensing Noise Estimation

Modeling Deformable Gradient Compositions for Single-Image Super-Resolution

no code implementations CVPR 2015 Yu Zhu, Yanning Zhang, Boyan Bonev, Alan L. Yuille

Based on the fact that singular primitive patches are more invariant to the scale change (i. e. have less ambiguity across different scales), we represent the non-singular primitives as compositions of singular ones, each of which is allowed some deformation.

Image Super-Resolution

Constraint Reduction using Marginal Polytope Diagrams for MAP LP Relaxations

no code implementations17 Dec 2013 Zhen Zhang, Qinfeng Shi, Yanning Zhang, Chunhua Shen, Anton Van Den Hengel

We show that using Marginal Polytope Diagrams allows the number of constraints to be reduced without loosening the LP relaxations.

Multi-image Blind Deblurring Using a Coupled Adaptive Sparse Prior

no code implementations CVPR 2013 Haichao Zhang, David Wipf, Yanning Zhang

This paper presents a robust algorithm for estimating a single latent sharp image given multiple blurry and/or noisy observations.

Deblurring

Part-Based Visual Tracking with Online Latent Structural Learning

no code implementations CVPR 2013 Rui Yao, Qinfeng Shi, Chunhua Shen, Yanning Zhang, Anton Van Den Hengel

Despite many advances made in the area, deformable targets and partial occlusions continue to represent key problems in visual tracking.

Structured Prediction Visual Tracking

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