Search Results for author: Nannan Wang

Found 90 papers, 33 papers with code

Thinking Racial Bias in Fair Forgery Detection: Models, Datasets and Evaluations

no code implementations19 Jul 2024 Decheng Liu, Zongqi Wang, Chunlei Peng, Nannan Wang, Ruimin Hu, Xinbo Gao

Due to the successful development of deep image generation technology, forgery detection plays a more important role in social and economic security.

Federated Face Forgery Detection Learning with Personalized Representation

no code implementations17 Jun 2024 Decheng Liu, Zhan Dang, Chunlei Peng, Nannan Wang, Ruimin Hu, Xinbo Gao

In addition, a personalized federated learning training strategy is utilized to update the parameters of the distributed detection model.

Personalized Federated Learning Representation Learning

Imperceptible Face Forgery Attack via Adversarial Semantic Mask

1 code implementation16 Jun 2024 Decheng Liu, Qixuan Su, Chunlei Peng, Nannan Wang, Xinbo Gao

With the great development of generative model techniques, face forgery detection draws more and more attention in the related field.

Adversarial Attack

Center-Sensitive Kernel Optimization for Efficient On-Device Incremental Learning

no code implementations13 Jun 2024 Dingwen Zhang, Yan Li, De Cheng, Nannan Wang, Junwei Han

Based on an empirical study on the knowledge intensity of the kernel elements of the neural network, we find that the center kernel is the key for maximizing the knowledge intensity for learning new data, while freezing the other kernel elements would get a good balance on the model's capacity for overcoming catastrophic forgetting.

Incremental Learning

Visual Prompt Tuning in Null Space for Continual Learning

no code implementations9 Jun 2024 Yue Lu, Shizhou Zhang, De Cheng, Yinghui Xing, Nannan Wang, Peng Wang, Yanning Zhang

Existing prompt-tuning methods have demonstrated impressive performances in continual learning (CL), by selecting and updating relevant prompts in the vision-transformer models.

Continual Learning Visual Prompt Tuning

InstructBrush: Learning Attention-based Instruction Optimization for Image Editing

no code implementations27 Mar 2024 Ruoyu Zhao, Qingnan Fan, Fei Kou, Shuai Qin, Hong Gu, Wei Wu, Pengcheng Xu, Mingrui Zhu, Nannan Wang, Xinbo Gao

Two key techniques are introduced into InstructBrush, Attention-based Instruction Optimization and Transformation-oriented Instruction Initialization, to address the limitations of the previous method in terms of inversion effects and instruction generalization.

Continual All-in-One Adverse Weather Removal with Knowledge Replay on a Unified Network Structure

1 code implementation12 Mar 2024 De Cheng, Yanling Ji, Dong Gong, Yan Li, Nannan Wang, Junwei Han, Dingwen Zhang

It considers the characteristics of the image restoration task with multiple degenerations in continual learning, and the knowledge for different degenerations can be shared and accumulated in the unified network structure.

Continual Learning Image Restoration +2

Robust Training of Federated Models with Extremely Label Deficiency

2 code implementations22 Feb 2024 Yonggang Zhang, Zhiqin Yang, Xinmei Tian, Nannan Wang, Tongliang Liu, Bo Han

Federated semi-supervised learning (FSSL) has emerged as a powerful paradigm for collaboratively training machine learning models using distributed data with label deficiency.

Exploring Homogeneous and Heterogeneous Consistent Label Associations for Unsupervised Visible-Infrared Person ReID

no code implementations1 Feb 2024 Lingfeng He, De Cheng, Nannan Wang, Xinbo Gao

In response, we introduce a Modality-Unified Label Transfer (MULT) module that simultaneously accounts for both homogeneous and heterogeneous fine-grained instance-level structures, yielding high-quality cross-modality label associations.

Person Re-Identification Pseudo Label +1

Bridging Generative and Discriminative Models for Unified Visual Perception with Diffusion Priors

no code implementations29 Jan 2024 Shiyin Dong, Mingrui Zhu, Kun Cheng, Nannan Wang, Xinbo Gao

Our purpose is to establish a unified visual perception framework, capitalizing on the potential synergies between generative and discriminative models.

Decoder Image Generation +4

Masked Attribute Description Embedding for Cloth-Changing Person Re-identification

1 code implementation11 Jan 2024 Chunlei Peng, Boyu Wang, Decheng Liu, Nannan Wang, Ruimin Hu, Xinbo Gao

To address this, we mask the clothing and color information in the personal attribute description extracted through an attribute detection model.

Attribute Cloth-Changing Person Re-Identification

Disentangled Prompt Representation for Domain Generalization

no code implementations CVPR 2024 De Cheng, Zhipeng Xu, Xinyang Jiang, Nannan Wang, Dongsheng Li, Xinbo Gao

Although there is a growing focus on VFM-based domain prompt tuning for DG effectively learning prompts that disentangle invariant features across all domains remains a major challenge.

Domain Generalization Language Modelling +2

Generating Handwritten Mathematical Expressions From Symbol Graphs: An End-to-End Pipeline

1 code implementation CVPR 2024 Yu Chen, Fei Gao, Yanguang Zhang, Maoying Qiao, Nannan Wang

To alleviate this challenge we propose a novel end-to-end G2I generation pipeline (i. e. graph - layout - mask - image) which requires no real masks or nondifferentiable alignment between layouts and masks.

Data Augmentation Image Generation

Point Deformable Network with Enhanced Normal Embedding for Point Cloud Analysis

no code implementations20 Dec 2023 Xingyilang Yin, Xi Yang, Liangchen Liu, Nannan Wang, Xinbo Gao

Additional offsets and modulation scalars are learned on the whole point features, which shift the deformable reference points to the regions of interest.

Adv-Diffusion: Imperceptible Adversarial Face Identity Attack via Latent Diffusion Model

1 code implementation18 Dec 2023 Decheng Liu, Xijun Wang, Chunlei Peng, Nannan Wang, Ruiming Hu, Xinbo Gao

Adversarial attacks involve adding perturbations to the source image to cause misclassification by the target model, which demonstrates the potential of attacking face recognition models.

Image Generation

SHaRPose: Sparse High-Resolution Representation for Human Pose Estimation

1 code implementation17 Dec 2023 Xiaoqi An, Lin Zhao, Chen Gong, Nannan Wang, Di Wang, Jian Yang

In this paper, we address the following question: "Only sparse human keypoint locations are detected for human pose estimation, is it really necessary to describe the whole image in a dense, high-resolution manner?"

Pose Estimation

Symmetrical Bidirectional Knowledge Alignment for Zero-Shot Sketch-Based Image Retrieval

1 code implementation16 Dec 2023 Decheng Liu, Xu Luo, Chunlei Peng, Nannan Wang, Ruimin Hu, Xinbo Gao

In this paper, we propose a novel Symmetrical Bidirectional Knowledge Alignment for zero-shot sketch-based image retrieval (SBKA).

Knowledge Distillation Retrieval +1

Multi-Scene Generalized Trajectory Global Graph Solver with Composite Nodes for Multiple Object Tracking

no code implementations14 Dec 2023 Yan Gao, Haojun Xu, Nannan Wang, Jie Li, Xinbo Gao

In addition to the previous method of treating objects as nodes, the network innovatively treats object trajectories as nodes for information interaction, improving the graph neural network's feature representation capability.

Multi-Object Tracking Multiple Object Tracking +1

DeepFidelity: Perceptual Forgery Fidelity Assessment for Deepfake Detection

2 code implementations7 Dec 2023 Chunlei Peng, Huiqing Guo, Decheng Liu, Nannan Wang, Ruimin Hu, Xinbo Gao

Considering the complexity of the quality distribution of both real and fake faces, we propose a novel Deepfake detection framework named DeepFidelity to adaptively distinguish real and fake faces with varying image quality by mining the perceptual forgery fidelity of face images.

DeepFake Detection Face Swapping

EtC: Temporal Boundary Expand then Clarify for Weakly Supervised Video Grounding with Multimodal Large Language Model

no code implementations5 Dec 2023 Guozhang Li, Xinpeng Ding, De Cheng, Jie Li, Nannan Wang, Xinbo Gao

To further clarify the noise of expanded boundaries, we combine mutual learning with a tailored proposal-level contrastive objective to use a learnable approach to harmonize a balance between incomplete yet clean (initial) and comprehensive yet noisy (expanded) boundaries for more precise ones.

Boundary Detection Language Modelling +3

HFORD: High-Fidelity and Occlusion-Robust De-identification for Face Privacy Protection

no code implementations15 Nov 2023 Dongxin Chen, Mingrui Zhu, Nannan Wang, Xinbo Gao

To disentangle the latent codes in the GAN inversion space, we introduce an Identity Disentanglement Module (IDM).

Attribute De-identification +1

Gradient constrained sharpness-aware prompt learning for vision-language models

no code implementations14 Sep 2023 Liangchen Liu, Nannan Wang, Dawei Zhou, Xinbo Gao, Decheng Liu, Xi Yang, Tongliang Liu

This paper targets a novel trade-off problem in generalizable prompt learning for vision-language models (VLM), i. e., improving the performance on unseen classes while maintaining the performance on seen classes.

Diff-Privacy: Diffusion-based Face Privacy Protection

no code implementations11 Sep 2023 Xiao He, Mingrui Zhu, Dongxin Chen, Nannan Wang, Xinbo Gao

In this paper, we unify the task of anonymization and visual identity information hiding and propose a novel face privacy protection method based on diffusion models, dubbed Diff-Privacy.

Denoising Scheduling

Human-Inspired Facial Sketch Synthesis with Dynamic Adaptation

1 code implementation ICCV 2023 Fei Gao, Yifan Zhu, Chang Jiang, Nannan Wang

Besides, different artists may use diverse drawing techniques and create multiple styles of sketches; but the style is globally consistent in a sketch.

Attention Consistency Refined Masked Frequency Forgery Representation for Generalizing Face Forgery Detection

1 code implementation21 Jul 2023 Decheng Liu, Tao Chen, Chunlei Peng, Nannan Wang, Ruimin Hu, Xinbo Gao

Due to the successful development of deep image generation technology, visual data forgery detection would play a more important role in social and economic security.

Image Generation

PRO-Face S: Privacy-preserving Reversible Obfuscation of Face Images via Secure Flow

no code implementations18 Jul 2023 Lin Yuan, Kai Liang, Xiao Pu, Yan Zhang, Jiaxu Leng, Tao Wu, Nannan Wang, Xinbo Gao

This paper proposes a novel paradigm for facial privacy protection that unifies multiple characteristics including anonymity, diversity, reversibility and security within a single lightweight framework.

Diversity Privacy Preserving

MMNet: Multi-Collaboration and Multi-Supervision Network for Sequential Deepfake Detection

no code implementations6 Jul 2023 Ruiyang Xia, Decheng Liu, Jie Li, Lin Yuan, Nannan Wang, Xinbo Gao

Advanced manipulation techniques have provided criminals with opportunities to make social panic or gain illicit profits through the generation of deceptive media, such as forged face images.

DeepFake Detection Face Swapping

Efficient Bilateral Cross-Modality Cluster Matching for Unsupervised Visible-Infrared Person ReID

no code implementations22 May 2023 De Cheng, Lingfeng He, Nannan Wang, Shizhou Zhang, Zhen Wang, Xinbo Gao

To this end, we propose a novel bilateral cluster matching-based learning framework to reduce the modality gap by matching cross-modality clusters.

Contrastive Learning Person Re-Identification

Unsupervised Visible-Infrared Person ReID by Collaborative Learning with Neighbor-Guided Label Refinement

no code implementations22 May 2023 De Cheng, Xiaojian Huang, Nannan Wang, Lingfeng He, Zhihui Li, Xinbo Gao

Unsupervised learning visible-infrared person re-identification (USL-VI-ReID) aims at learning modality-invariant features from unlabeled cross-modality dataset, which is crucial for practical applications in video surveillance systems.

Person Re-Identification

Adapt and Align to Improve Zero-Shot Sketch-Based Image Retrieval

no code implementations9 May 2023 Shiyin Dong, Mingrui Zhu, Nannan Wang, Xinbo Gao

Zero-shot sketch-based image retrieval (ZS-SBIR) is challenging due to the cross-domain nature of sketches and photos, as well as the semantic gap between seen and unseen image distributions.

Retrieval Sketch-Based Image Retrieval +1

Semantic-aware Generation of Multi-view Portrait Drawings

1 code implementation4 May 2023 Biao Ma, Fei Gao, Chang Jiang, Nannan Wang, Gang Xu

Our motivation is that facial semantic labels are view-consistent and correlate with drawing techniques.

3D-Aware Image Synthesis Data Augmentation

Boosting Weakly-Supervised Temporal Action Localization with Text Information

1 code implementation CVPR 2023 Guozhang Li, De Cheng, Xinpeng Ding, Nannan Wang, Xiaoyu Wang, Xinbo Gao

For the discriminative objective, we propose a Text-Segment Mining (TSM) mechanism, which constructs a text description based on the action class label, and regards the text as the query to mine all class-related segments.

Sentence Weakly-supervised Temporal Action Localization +1

Weakly-Supervised Temporal Action Localization with Bidirectional Semantic Consistency Constraint

1 code implementation25 Apr 2023 Guozhang Li, De Cheng, Xinpeng Ding, Nannan Wang, Jie Li, Xinbo Gao

The proposed Bi-SCC firstly adopts a temporal context augmentation to generate an augmented video that breaks the correlation between positive actions and their co-scene actions in the inter-video; Then, a semantic consistency constraint (SCC) is used to enforce the predictions of the original video and augmented video to be consistent, hence suppressing the co-scene actions.

Weakly-supervised Temporal Action Localization Weakly Supervised Temporal Action Localization

Masked and Adaptive Transformer for Exemplar Based Image Translation

1 code implementation CVPR 2023 Chang Jiang, Fei Gao, Biao Ma, YuHao Lin, Nannan Wang, Gang Xu

To overcome this challenge, we improve the accuracy of matching on the one hand, and diminish the role of matching in image generation on the other hand.

Image Generation Semantic correspondence +1

Few-shot Face Image Translation via GAN Prior Distillation

no code implementations28 Jan 2023 Ruoyu Zhao, Mingrui Zhu, Xiaoyu Wang, Nannan Wang

GPD contains two models: a teacher network with GAN Prior and a student network that fulfills end-to-end translation.

Knowledge Distillation Translation

Few-shot Font Generation by Learning Style Difference and Similarity

no code implementations24 Jan 2023 Xiao He, Mingrui Zhu, Nannan Wang, Xinbo Gao, Heng Yang

To address this issue, we propose a novel font generation approach by learning the Difference between different styles and the Similarity of the same style (DS-Font).

Contrastive Learning Font Generation

All-to-key Attention for Arbitrary Style Transfer

1 code implementation ICCV 2023 Mingrui Zhu, Xiao He, Nannan Wang, Xiaoyu Wang, Xinbo Gao

In this paper, we propose a novel all-to-key attention mechanism -- each position of content features is matched to stable key positions of style features -- that is more in line with the characteristics of style transfer.

Position Style Transfer

Neighbour Consistency Guided Pseudo-Label Refinement for Unsupervised Person Re-Identification

no code implementations30 Nov 2022 De Cheng, Haichun Tai, Nannan Wang, Zhen Wang, Xinbo Gao

In this paper, we propose a Neighbour Consistency guided Pseudo Label Refinement (NCPLR) framework, which can be regarded as a transductive form of label propagation under the assumption that the prediction of each example should be similar to its nearest neighbours'.

Clustering Person Retrieval +3

VideoReTalking: Audio-based Lip Synchronization for Talking Head Video Editing In the Wild

1 code implementation27 Nov 2022 Kun Cheng, Xiaodong Cun, Yong Zhang, Menghan Xia, Fei Yin, Mingrui Zhu, Xuan Wang, Jue Wang, Nannan Wang

Our system disentangles this objective into three sequential tasks: (1) face video generation with a canonical expression; (2) audio-driven lip-sync; and (3) face enhancement for improving photo-realism.

Video Editing Video Generation

NAR-Former: Neural Architecture Representation Learning towards Holistic Attributes Prediction

1 code implementation CVPR 2023 Yun Yi, Haokui Zhang, Wenze Hu, Nannan Wang, Xiaoyu Wang

In this paper, we propose a neural architecture representation model that can be used to estimate these attributes holistically.

Representation Learning

Class-Dependent Label-Noise Learning with Cycle-Consistency Regularization Feature Space

1 code implementation NIPS 2022 De Cheng, Yixiong Ning, Nannan Wang, Xinbo Gao, Heng Yang, Yuxuan Du, Bo Han, Tongliang Liu

We show that the cycle-consistency regularization helps to minimize the volume of the transition matrix T indirectly without exploiting the estimated noisy class posterior, which could further encourage the estimated transition matrix T to converge to its optimal solution.

FedForgery: Generalized Face Forgery Detection with Residual Federated Learning

1 code implementation18 Oct 2022 Decheng Liu, Zhan Dang, Chunlei Peng, Yu Zheng, Shuang Li, Nannan Wang, Xinbo Gao

Experiments conducted on publicly available face forgery detection datasets prove the superior performance of the proposed FedForgery.

Federated Learning Image Generation

Strength-Adaptive Adversarial Training

no code implementations4 Oct 2022 Chaojian Yu, Dawei Zhou, Li Shen, Jun Yu, Bo Han, Mingming Gong, Nannan Wang, Tongliang Liu

Firstly, applying a pre-specified perturbation budget on networks of various model capacities will yield divergent degree of robustness disparity between natural and robust accuracies, which deviates from robust network's desideratum.

Adversarial Robustness Scheduling

Improving Adversarial Robustness via Mutual Information Estimation

1 code implementation25 Jul 2022 Dawei Zhou, Nannan Wang, Xinbo Gao, Bo Han, Xiaoyu Wang, Yibing Zhan, Tongliang Liu

To alleviate this negative effect, in this paper, we investigate the dependence between outputs of the target model and input adversarial samples from the perspective of information theory, and propose an adversarial defense method.

Adversarial Defense Adversarial Robustness +1

TransFA: Transformer-based Representation for Face Attribute Evaluation

1 code implementation12 Jul 2022 Decheng Liu, Weijie He, Chunlei Peng, Nannan Wang, Jie Li, Xinbo Gao

The multiple branches transformer is employed to explore the inter-correlation between different attributes in similar semantic regions for attribute feature learning.

Attribute Multi-Label Classification +1

Spatial-Temporal Frequency Forgery Clue for Video Forgery Detection in VIS and NIR Scenario

no code implementations5 Jul 2022 Yukai Wang, Chunlei Peng, Decheng Liu, Nannan Wang, Xinbo Gao

In recent years, with the rapid development of face editing and generation, more and more fake videos are circulating on social media, which has caused extreme public concerns.

Instance-Dependent Label-Noise Learning with Manifold-Regularized Transition Matrix Estimation

no code implementations CVPR 2022 De Cheng, Tongliang Liu, Yixiong Ning, Nannan Wang, Bo Han, Gang Niu, Xinbo Gao, Masashi Sugiyama

In label-noise learning, estimating the transition matrix has attracted more and more attention as the matrix plays an important role in building statistically consistent classifiers.

Robust Single Image Dehazing Based on Consistent and Contrast-Assisted Reconstruction

no code implementations29 Mar 2022 De Cheng, Yan Li, Dingwen Zhang, Nannan Wang, Xinbo Gao, Jiande Sun

To properly address this problem, we propose a novel density-variational learning framework to improve the robustness of the image dehzing model assisted by a variety of negative hazy images, to better deal with various complex hazy scenarios.

Image Dehazing Single Image Dehazing

Towards Semi-Supervised Deep Facial Expression Recognition with An Adaptive Confidence Margin

1 code implementation CVPR 2022 Hangyu Li, Nannan Wang, Xi Yang, Xiaoyu Wang, Xinbo Gao

In this paper, we learn an Adaptive Confidence Margin (Ada-CM) to fully leverage all unlabeled data for semi-supervised deep facial expression recognition.

Facial Expression Recognition Facial Expression Recognition (FER)

Semi-parametric Makeup Transfer via Semantic-aware Correspondence

1 code implementation4 Mar 2022 Mingrui Zhu, Yun Yi, Nannan Wang, Xiaoyu Wang, Xinbo Gao

The large discrepancy between the source non-makeup image and the reference makeup image is one of the key challenges in makeup transfer.

Decoder

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.

Clustering Contrastive Learning +3

Modeling Adversarial Noise for Adversarial Defense

no code implementations29 Sep 2021 Dawei Zhou, Nannan Wang, Bo Han, Tongliang Liu

Deep neural networks have been demonstrated to be vulnerable to adversarial noise, promoting the development of defense against adversarial attacks.

Adversarial Defense

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

Modeling Adversarial Noise for Adversarial Training

1 code implementation21 Sep 2021 Dawei Zhou, Nannan Wang, Bo Han, Tongliang Liu

Deep neural networks have been demonstrated to be vulnerable to adversarial noise, promoting the development of defense against adversarial attacks.

Adversarial Defense

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 Video Grounding

Exploring Set Similarity for Dense Self-supervised Representation Learning

no code implementations CVPR 2022 Zhaoqing Wang, Qiang Li, Guoxin Zhang, Pengfei Wan, Wen Zheng, Nannan Wang, Mingming Gong, Tongliang Liu

By considering the spatial correspondence, dense self-supervised representation learning has achieved superior performance on various dense prediction tasks.

Instance Segmentation Keypoint Detection +5

Kernel Mean Estimation by Marginalized Corrupted Distributions

no code implementations10 Jul 2021 Xiaobo Xia, Shuo Shan, Mingming Gong, Nannan Wang, Fei Gao, Haikun Wei, Tongliang Liu

Estimating the kernel mean in a reproducing kernel Hilbert space is a critical component in many kernel learning algorithms.

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 Adversarial Robustness

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.

Adversarial Robustness

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.

Adversarial Robustness 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

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

Extended T: Learning with Mixed Closed-set and Open-set Noisy Labels

no code implementations2 Dec 2020 Xiaobo Xia, Tongliang Liu, Bo Han, Nannan Wang, Jiankang Deng, Jiatong Li, Yinian Mao

The traditional transition matrix is limited to model closed-set label noise, where noisy training data has true class labels within the noisy label set.

Class2Simi: A New Perspective on Learning with Label Noise

no code implementations28 Sep 2020 Songhua Wu, Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Nannan Wang, Haifeng Liu, Gang Niu

It is worthwhile to perform the transformation: We prove that the noise rate for the noisy similarity labels is lower than that of the noisy class labels, because similarity labels themselves are robust to noise.

CoFF: Cooperative Spatial Feature Fusion for 3D Object Detection on Autonomous Vehicles

no code implementations24 Sep 2020 Jingda Guo, Dominic Carrillo, Sihai Tang, Qi Chen, Qing Yang, Song Fu, Xi Wang, Nannan Wang, Paparao Palacharla

To reduce the amount of transmitted data, feature map based fusion is recently proposed as a practical solution to cooperative 3D object detection by autonomous vehicles.

3D Object Detection Autonomous Vehicles +2

Part-dependent Label Noise: Towards Instance-dependent Label Noise

1 code implementation NeurIPS 2020 Xiaobo Xia, Tongliang Liu, Bo Han, Nannan Wang, Mingming Gong, Haifeng Liu, Gang Niu, DaCheng Tao, Masashi Sugiyama

Learning with the \textit{instance-dependent} label noise is challenging, because it is hard to model such real-world noise.

Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels

no code implementations14 Jun 2020 Songhua Wu, Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Nannan Wang, Haifeng Liu, Gang Niu

To give an affirmative answer, in this paper, we propose a framework called Class2Simi: it transforms data points with noisy class labels to data pairs with noisy similarity labels, where a similarity label denotes whether a pair shares the class label or not.

Contrastive Learning Learning with noisy labels +1

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.

Attribute Hallucination +1

Multi-Class Classification from Noisy-Similarity-Labeled Data

no code implementations16 Feb 2020 Songhua Wu, Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Nannan Wang, Haifeng Liu, Gang Niu

We further estimate the transition matrix from only noisy data and build a novel learning system to learn a classifier which can assign noise-free class labels for instances.

Classification General Classification +1

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

Are Anchor Points Really Indispensable in Label-Noise Learning?

1 code implementation NeurIPS 2019 Xiaobo Xia, Tongliang Liu, Nannan Wang, Bo Han, Chen Gong, Gang Niu, Masashi Sugiyama

Existing theories have shown that the transition matrix can be learned by exploiting \textit{anchor points} (i. e., data points that belong to a specific class almost surely).

Learning with noisy labels

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

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 +1

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

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 Modelling Face Alignment +4

Cannot find the paper you are looking for? You can Submit a new open access paper.