Search Results for author: Xinbo Gao

Found 62 papers, 11 papers with code

Self-supervised Contrastive Attributed Graph Clustering

no code implementations15 Oct 2021 Wei Xia, Quanxue Gao, Ming Yang, Xinbo Gao

Thus, for the OOS nodes, SCAGC can directly calculate their clustering labels.

Infrared Small-Dim Target Detection with Transformer under Complex Backgrounds

no code implementations29 Sep 2021 Fangcen Liu, Chenqiang Gao, Fang Chen, Deyu Meng, WangMeng Zuo, Xinbo Gao

To this end, we propose a new infrared small-dim target detection method with the transformer.

Hybrid Dynamic Contrast and Probability Distillation for Unsupervised Person Re-Id

no code implementations29 Sep 2021 De Cheng, Jingyu Zhou, Nannan Wang, Xinbo Gao

However, since person Re-Id is an open-set problem, the clustering based methods often leave out lots of outlier instances or group the instances into the wrong clusters, thus they can not make full use of the training samples as a whole.

Contrastive Learning Metric Learning +2

Single Image Dehazing with An Independent Detail-Recovery Network

1 code implementation22 Sep 2021 Yan Li, De Cheng, Jiande Sun, Dingwen Zhang, Nannan Wang, Xinbo Gao

In this paper, we propose a single image dehazing method with an independent Detail Recovery Network (DRN), which considers capturing the details from the input image over a separate network and then integrates them into a coarse dehazed image.

Image Dehazing Single Image Dehazing

Stimuli-Aware Visual Emotion Analysis

no code implementations4 Sep 2021 Jingyuan Yang, Jie Li, Xiumei Wang, Yuxuan Ding, Xinbo Gao

Then, we design three specific networks, i. e., Global-Net, Semantic-Net and Expression-Net, to extract distinct emotional features from different stimuli simultaneously.

Emotion Recognition

Support-Set Based Cross-Supervision for Video Grounding

no code implementations ICCV 2021 Xinpeng Ding, Nannan Wang, Shiwei Zhang, De Cheng, Xiaomeng Li, Ziyuan Huang, Mingqian Tang, Xinbo Gao

The contrastive objective aims to learn effective representations by contrastive learning, while the caption objective can train a powerful video encoder supervised by texts.

Contrastive Learning

Effective and Efficient Graph Learning for Multi-view Clustering

no code implementations15 Aug 2021 Quanxue Gao, Wei Xia, Xinbo Gao, DaCheng Tao

Despite the impressive clustering performance and efficiency in characterizing both the relationship between data and cluster structure, existing graph-based multi-view clustering methods still have the following drawbacks.

Graph Learning

Multiple Graph Learning for Scalable Multi-view Clustering

no code implementations29 Jun 2021 Tianyu Jiang, Quanxue Gao, Xinbo Gao

Specifically, we construct a hidden and tractable large graph by anchor graph for each view and well exploit complementary information embedded in anchor graphs of different views by tensor Schatten p-norm regularizer.

graph construction Graph Learning

A Circular-Structured Representation for Visual Emotion Distribution Learning

no code implementations CVPR 2021 Jingyuan Yang, Jie Li, Leida Li, Xiumei Wang, Xinbo Gao

Visual Emotion Analysis (VEA) has attracted increasing attention recently with the prevalence of sharing images on social networks.

Emotion Recognition

TSGCNet: Discriminative Geometric Feature Learning With Two-Stream Graph Convolutional Network for 3D Dental Model Segmentation

no code implementations CVPR 2021 Lingming Zhang, Yue Zhao, Deyu Meng, Zhiming Cui, Chenqiang Gao, Xinbo Gao, Chunfeng Lian, Dinggang Shen

State-of-the-art methods directly concatenate the raw attributes of 3D inputs, namely coordinates and normal vectors of mesh cells, to train a single-stream network for fully-automated tooth segmentation.

Graph Learning

Learning the Non-Differentiable Optimization for Blind Super-Resolution

no code implementations CVPR 2021 Zheng Hui, Jie Li, Xiumei Wang, Xinbo Gao

Instead of considering iterative strategy, we make the blur kernel predictor trainable in the whole blind SR model, in which AMNet is well-trained.

Super-Resolution

Improving White-box Robustness of Pre-processing Defenses via Joint Adversarial Training

no code implementations10 Jun 2021 Dawei Zhou, Nannan Wang, Xinbo Gao, Bo Han, Jun Yu, Xiaoyu Wang, Tongliang Liu

However, pre-processing methods may suffer from the robustness degradation effect, in which the defense reduces rather than improving the adversarial robustness of a target model in a white-box setting.

Adversarial Defense

Towards Defending against Adversarial Examples via Attack-Invariant Features

no code implementations9 Jun 2021 Dawei Zhou, Tongliang Liu, Bo Han, Nannan Wang, Chunlei Peng, Xinbo Gao

However, given the continuously evolving attacks, models trained on seen types of adversarial examples generally cannot generalize well to unseen types of adversarial examples.

Removing Adversarial Noise in Class Activation Feature Space

no code implementations ICCV 2021 Dawei Zhou, Nannan Wang, Chunlei Peng, Xinbo Gao, Xiaoyu Wang, Jun Yu, Tongliang Liu

Then, we train a denoising model to minimize the distances between the adversarial examples and the natural examples in the class activation feature space.

Denoising

Drafting and Revision: Laplacian Pyramid Network for Fast High-Quality Artistic Style Transfer

2 code implementations CVPR 2021 Tianwei Lin, Zhuoqi Ma, Fu Li, Dongliang He, Xin Li, Errui Ding, Nannan Wang, Jie Li, Xinbo Gao

Inspired by the common painting process of drawing a draft and revising the details, we introduce a novel feed-forward method named Laplacian Pyramid Network (LapStyle).

Style Transfer

Transitive Learning: Exploring the Transitivity of Degradations for Blind Super-Resolution

1 code implementation29 Mar 2021 Yuanfei Huang, Jie Li, Yanting Hu, Xinbo Gao, Wen Lu

We then propose a novel Transitive Learning method for blind Super-Resolution on transitive degradations (TLSR), by adaptively inferring a transitive transformation function to solve the unknown degradations without any iterative operations in inference.

Super-Resolution

ADD-Defense: Towards Defending Widespread Adversarial Examples via Perturbation-Invariant Representation

no code implementations1 Jan 2021 Dawei Zhou, Tongliang Liu, Bo Han, Nannan Wang, Xinbo Gao

Motivated by this observation, we propose a defense framework ADD-Defense, which extracts the invariant information called \textit{perturbation-invariant representation} (PIR) to defend against widespread adversarial examples.

Syncretic Modality Collaborative Learning for Visible Infrared Person Re-Identification

no code implementations ICCV 2021 Ziyu Wei, Xi Yang, Nannan Wang, Xinbo Gao

Visible infrared person re-identification (VI-REID) aims to match pedestrian images between the daytime visible and nighttime infrared camera views.

Person Re-Identification

TSGCNet: Discriminative Geometric Feature Learning with Two-Stream GraphConvolutional Network for 3D Dental Model Segmentation

no code implementations26 Dec 2020 Lingming Zhang, Yue Zhao, Deyu Meng, Zhiming Cui, Chenqiang Gao, Xinbo Gao, Chunfeng Lian, Dinggang Shen

State-of-the-art methods directly concatenate the raw attributes of 3D inputs, namely coordinates and normal vectors of mesh cells, to train a single-stream network for fully-automated tooth segmentation.

Graph Learning

D-Unet: A Dual-encoder U-Net for Image Splicing Forgery Detection and Localization

no code implementations3 Dec 2020 Xiuli Bi, Yanbin Liu, Bin Xiao, Weisheng Li, Chi-Man Pun, Guoyin Wang, Xinbo Gao

The unfixed encoder autonomously learns the image fingerprints that differentiate between the tampered and non-tampered regions, whereas the fixed encoder intentionally provides the direction information that assists the learning and detection of the network.

Interpretable Detail-Fidelity Attention Network for Single Image Super-Resolution

1 code implementation28 Sep 2020 Yuanfei Huang, Jie Li, Xinbo Gao, Yanting Hu, Wen Lu

To solve them, we propose a purposeful and interpretable detail-fidelity attention network to progressively process these smoothes and details in divide-and-conquer manner, which is a novel and specific prospect of image super-resolution for the purpose on improving the detail fidelity, instead of blindly designing or employing the deep CNNs architectures for merely feature representation in local receptive fields.

Image Super-Resolution

Tasks Integrated Networks: Joint Detection and Retrieval for Image Search

no code implementations3 Sep 2020 Lei Zhang, Zhenwei He, Yi Yang, Liang Wang, Xinbo Gao

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 image are manually or automatically pre-cropped exactly.

Image Retrieval

Collaborative Boundary-aware Context Encoding Networks for Error Map Prediction

no code implementations25 Jun 2020 Zhenxi Zhang, Chunna Tian, Jie Li, Zhusi Zhong, Zhicheng Jiao, Xinbo Gao

Further, we propose a context encoding module to utilize the global predictor from the error map to enhance the feature representation and regularize the networks.

Medical Image Segmentation

Multi-Margin based Decorrelation Learning for Heterogeneous Face Recognition

no code implementations25 May 2020 Bing Cao, Nannan Wang, Xinbo Gao, Jie Li, Zhifeng Li

Heterogeneous face recognition (HFR) refers to matching face images acquired from different domains with wide applications in security scenarios.

Face Recognition Heterogeneous Face Recognition +1

Facial Attribute Capsules for Noise Face Super Resolution

no code implementations16 Feb 2020 Jingwei Xin, Nannan Wang, Xinrui Jiang, Jie Li, Xinbo Gao, Zhifeng Li

In the SR processing, we first generated a group of FACs from the input LR face, and then reconstructed the HR face from this group of FACs.

Image Super-Resolution

Video Face Super-Resolution with Motion-Adaptive Feedback Cell

no code implementations15 Feb 2020 Jingwei Xin, Nannan Wang, Jie Li, Xinbo Gao, Zhifeng Li

Current state-of-the-art CNN methods usually treat the VSR problem as a large number of separate multi-frame super-resolution tasks, at which a batch of low resolution (LR) frames is utilized to generate a single high resolution (HR) frame, and running a slide window to select LR frames over the entire video would obtain a series of HR frames.

Motion Compensation Motion Estimation +2

Asynchronous Tracking-by-Detection on Adaptive Time Surfaces for Event-based Object Tracking

no code implementations13 Feb 2020 Haosheng Chen, Qiangqiang Wu, Yanjie Liang, Xinbo Gao, Hanzi Wang

To achieve this goal, we present an Adaptive Time-Surface with Linear Time Decay (ATSLTD) event-to-frame conversion algorithm, which asynchronously and effectively warps the spatio-temporal information of asynchronous retinal events to a sequence of ATSLTD frames with clear object contours.

Object Tracking

Image Fine-grained Inpainting

2 code implementations7 Feb 2020 Zheng Hui, Jie Li, Xiumei Wang, Xinbo Gao

Besides, we devise a geometrical alignment constraint item to compensate for the pixel-based distance between prediction features and ground-truth ones.

Facial Inpainting Fine-Grained Image Inpainting

Lightweight Image Super-Resolution with Information Multi-distillation Network

1 code implementation26 Sep 2019 Zheng Hui, Xinbo Gao, Yunchu Yang, Xiumei Wang

In recent years, single image super-resolution (SISR) methods using deep convolution neural network (CNN) have achieved impressive results.

Image Super-Resolution

Progressive Perception-Oriented Network for Single Image Super-Resolution

1 code implementation24 Jul 2019 Zheng Hui, Jie Li, Xinbo Gao, Xiumei Wang

In this paper, we propose a novel perceptual image super-resolution method that progressively generates visually high-quality results by constructing a stage-wise network.

Image Super-Resolution

Reconstructing Perceived Images from Brain Activity by Visually-guided Cognitive Representation and Adversarial Learning

no code implementations27 Jun 2019 Ziqi Ren, Jie Li, Xuetong Xue, Xin Li, Fan Yang, Zhicheng Jiao, Xinbo Gao

In addition, we introduce a novel three-stage learning approach which enables the (cognitive) encoder to gradually distill useful knowledge from the paired (visual) encoder during the learning process.

Image Reconstruction Knowledge Distillation +1

An Attention-Guided Deep Regression Model for Landmark Detection in Cephalograms

no code implementations17 Jun 2019 Zhusi Zhong, Jie Li, Zhenxi Zhang, Zhicheng Jiao, Xinbo Gao

We train the deep encoder-decoder for landmark detection, and combine global landmark configuration with local high-resolution feature responses.

Deep Multi-scale Discriminative Networks for Double JPEG Compression Forensics

no code implementations4 Apr 2019 Cheng Deng, Zhao Li, Xinbo Gao, DaCheng Tao

In this area, extracting effective statistical characteristics from a JPEG image for classification remains a challenge.

General Classification

Triplet-Based Deep Hashing Network for Cross-Modal Retrieval

no code implementations4 Apr 2019 Cheng Deng, Zhaojia Chen, Xianglong Liu, Xinbo Gao, DaCheng Tao

Given the benefits of its low storage requirements and high retrieval efficiency, hashing has recently received increasing attention.

Cross-Modal Retrieval Semantic Similarity +1

Stacked Semantic-Guided Network for Zero-Shot Sketch-Based Image Retrieval

no code implementations3 Apr 2019 Hao Wang, Cheng Deng, Xinxu Xu, Wei Liu, Xinbo Gao, DaCheng Tao

Previous works mostly focus on a generative approach that takes a highly abstract and sparse sketch as input and then synthesizes the corresponding natural image.

Sketch-Based Image Retrieval Transfer Learning

Transfer Adaptation Learning: A Decade Survey

no code implementations12 Mar 2019 Lei Zhang, Xinbo Gao

Domain is referred to as the state of the world at a certain moment.

A Gated Peripheral-Foveal Convolutional Neural Network for Unified Image Aesthetic Prediction

no code implementations19 Dec 2018 Xiaodan Zhang, Xinbo Gao, Wen Lu, Lihuo He

The former aims to mimic the functions of peripheral vision to encode the holistic information and provide the attended regions.

Channel-wise and Spatial Feature Modulation Network for Single Image Super-Resolution

no code implementations28 Sep 2018 Yanting Hu, Jie Li, Yuanfei Huang, Xinbo Gao

To capture more informative features and maintain long-term information for image super-resolution, we propose a channel-wise and spatial feature modulation (CSFM) network in which a sequence of feature-modulation memory (FMM) modules is cascaded with a densely connected structure to transform low-resolution features to high informative features.

Image Reconstruction Image Super-Resolution

Saliency deep embedding for aurora image search

no code implementations23 May 2018 Xi Yang, Xinbo Gao, Bin Song, Nannan Wang, Dong Yang

In this paper, we aim to explore a new search method for images captured with circular fisheye lens, especially the aurora images.

Image Retrieval Region Proposal

Self-Supervised Adversarial Hashing Networks for Cross-Modal Retrieval

no code implementations CVPR 2018 Chao Li, Cheng Deng, Ning li, Wei Liu, Xinbo Gao, DaCheng Tao

In addition, we harness a self-supervised semantic network to discover high-level semantic information in the form of multi-label annotations.

Cross-Modal Retrieval

Fast and Accurate Single Image Super-Resolution via Information Distillation Network

1 code implementation CVPR 2018 Zheng Hui, Xiumei Wang, Xinbo Gao

Recently, deep convolutional neural networks (CNNs) have been demonstrated remarkable progress on single image super-resolution.

Image Super-Resolution

Single Image Super-Resolution via Cascaded Multi-Scale Cross Network

no code implementations24 Feb 2018 Yanting Hu, Xinbo Gao, Jie Li, Yuanfei Huang, Hanzi Wang

To improve information flow and to capture sufficient knowledge for reconstructing the high-frequency details, we propose a cascaded multi-scale cross network (CMSC) in which a sequence of subnetworks is cascaded to infer high resolution features in a coarse-to-fine manner.

Image Reconstruction Image Super-Resolution

Restricting Greed in Training of Generative Adversarial Network

no code implementations28 Nov 2017 Haoxuan You, Zhicheng Jiao, Haojun Xu, Jie Li, Ying Wang, Xinbo Gao

Generative adversarial network (GAN) has gotten wide re-search interest in the field of deep learning.

Hierarchical Multimodal LSTM for Dense Visual-Semantic Embedding

no code implementations ICCV 2017 Zhenxing Niu, Mo Zhou, Le Wang, Xinbo Gao, Gang Hua

We address the problem of dense visual-semantic embedding that maps not only full sentences and whole images but also phrases within sentences and salient regions within images into a multimodal embedding space.

Hierarchical structure

Random Sampling for Fast Face Sketch Synthesis

no code implementations8 Jan 2017 Nannan Wang, Xinbo Gao, Jie Li

The most time-consuming or main computation complexity for exemplar-based face sketch synthesis methods lies in the neighbor selection process.

Face Hallucination Face Sketch Synthesis

Sparse Graphical Representation based Discriminant Analysis for Heterogeneous Face Recognition

no code implementations1 Jul 2016 Chunlei Peng, Xinbo Gao, Nannan Wang, Jie Li

An adaptive sparse graphical representation scheme is designed to represent heterogeneous face images, where a Markov networks model is constructed to generate adaptive sparse vectors.

Face Recognition Heterogeneous Face Recognition

Ordinal Regression With Multiple Output CNN for Age Estimation

no code implementations CVPR 2016 Zhenxing Niu, Mo Zhou, Le Wang, Xinbo Gao, Gang Hua

To address the non-stationary property of aging patterns, age estimation can be cast as an ordinal regression problem.

Age Estimation General Classification

Training-Free Synthesized Face Sketch Recognition Using Image Quality Assessment Metrics

no code implementations25 Mar 2016 Nannan Wang, Jie Li, Leiyu Sun, Bin Song, Xinbo Gao

In this paper, we proposed a synthesized face sketch recognition framework based on full-reference image quality assessment metrics.

Face Recognition Face Sketch Synthesis +2

Graphical Representation for Heterogeneous Face Recognition

no code implementations2 Mar 2015 Chunlei Peng, Xinbo Gao, Nannan Wang, Jie Li

Heterogeneous face recognition (HFR) refers to matching face images acquired from different sources (i. e., different sensors or different wavelengths) for identification.

Face Recognition Heterogeneous Face Recognition

Facial Feature Point Detection: A Comprehensive Survey

no code implementations4 Oct 2014 Nannan Wang, Xinbo Gao, DaCheng Tao, Xuelong. Li

CLM-based methods consist of a shape model and a number of local experts, each of which is utilized to detect a facial feature point.

3D FACE MODELING Face Alignment +2

Semi-supervised Relational Topic Model for Weakly Annotated Image Recognition in Social Media

no code implementations CVPR 2014 Zhenxing Niu, Gang Hua, Xinbo Gao, Qi Tian

In such way, we can efficiently leverage the loosely related tags, and build an intermediate level representation for a collection of weakly annotated images.

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