Search Results for author: Tieniu Tan

Found 77 papers, 20 papers with code

Employing Multi-Estimations for Weakly-Supervised Semantic Segmentation

no code implementations ECCV 2020 Junsong Fan, Zhao-Xiang Zhang, Tieniu Tan

Instead of struggling to refine a single seed, we propose a novel approach to alleviate the inaccurate seed problem by leveraging the segmentation model's robustness to learn from multiple seeds.

Weakly-Supervised Semantic Segmentation

Prediction and Recovery for Adaptive Low-Resolution Person Re-Identification

no code implementations ECCV 2020 Ke Han, Yan Huang, Zerui Chen, Liang Wang, Tieniu Tan

In this paper, we propose a novel Prediction, Recovery and Identification (PRI) model for LR re-id, which adaptively recovers missing details by predicting a preferable scale factor based on the image content.

Person Re-Identification Super-Resolution

Disentangled Federated Learning for Tackling Attributes Skew via Invariant Aggregation and Diversity Transferring

no code implementations14 Jun 2022 Zhengquan Luo, Yunlong Wang, Zilei Wang, Zhenan Sun, Tieniu Tan

Attributes skew hinders the current federated learning (FL) frameworks from consistent optimization directions among the clients, which inevitably leads to performance reduction and unstable convergence.

Federated Learning

Learning the Degradation Distribution for Blind Image Super-Resolution

no code implementations CVPR 2022 Zhengxiong Luo, Yan Huang, Shang Li, Liang Wang, Tieniu Tan

Compared with previous deterministic degradation models, PDM could model more diverse degradations and generate HR-LR pairs that may better cover the various degradations of test images, and thus prevent the SR model from over-fitting to specific ones.

Image Super-Resolution

Generalizable Person Re-Identification via Self-Supervised Batch Norm Test-Time Adaption

no code implementations1 Mar 2022 Ke Han, Chenyang Si, Yan Huang, Liang Wang, Tieniu Tan

In this paper, we investigate the generalization problem of person re-identification (re-id), whose major challenge is the distribution shift on an unseen domain.

Generalizable Person Re-identification

DRAN: Detailed Region-Adaptive Normalization for Conditional Image Synthesis

no code implementations29 Sep 2021 Yueming Lyu, Peibin Chen, Jingna Sun, Xu Wang, Jing Dong, Tieniu Tan

To evaluate the effectiveness and generalization ability of DRAN, we conduct a set of experiments on makeup transfer and semantic image synthesis.

Facial Makeup Transfer Image Generation +1

Generalizable Person Re-identification Without Demographics

no code implementations29 Sep 2021 Yifan Zhang, Feng Li, Zhang Zhang, Liang Wang, DaCheng Tao, Tieniu Tan

However, the convex condition of KL DRO may not hold for overparameterized neural networks, such that applying KL DRO often fails to generalize under distribution shifts in real scenarios.

Generalizable Person Re-identification

Cross-Domain Cross-Set Few-Shot Learning via Learning Compact and Aligned Representations

no code implementations29 Sep 2021 Wentao Chen, Zhang Zhang, Wei Wang, Liang Wang, Zilei Wang, Tieniu Tan

Few-shot learning (FSL) aims to recognize novel query examples with a small support set through leveraging prior knowledge learned from a large-scale training set.

Few-Shot Learning

Adaptive Dilated Convolution For Human Pose Estimation

no code implementations22 Jul 2021 Zhengxiong Luo, Zhicheng Wang, Yan Huang, Liang Wang, Tieniu Tan, Erjin Zhou

It can generate and fuse multi-scale features of the same spatial sizes by setting different dilation rates for different channels.

Pose Estimation

Neighbor-view Enhanced Model for Vision and Language Navigation

1 code implementation15 Jul 2021 Dong An, Yuankai Qi, Yan Huang, Qi Wu, Liang Wang, Tieniu Tan

Specifically, our NvEM utilizes a subject module and a reference module to collect contexts from neighbor views.

Vision and Language Navigation

GAIA: A Transfer Learning System of Object Detection that Fits Your Needs

1 code implementation CVPR 2021 Xingyuan Bu, Junran Peng, Junjie Yan, Tieniu Tan, Zhaoxiang Zhang

Transfer learning with pre-training on large-scale datasets has played an increasingly significant role in computer vision and natural language processing recently.

Computer Vision Natural Language Processing +3

Transferable Sparse Adversarial Attack

1 code implementation CVPR 2022 Ziwen He, Wei Wang, Jing Dong, Tieniu Tan

The experiment shows that our method has improved the transferability by a large margin under a similar sparsity setting compared with state-of-the-art methods.

Adversarial Attack Quantization

End-to-end Alternating Optimization for Blind Super Resolution

1 code implementation14 May 2021 Zhengxiong Luo, Yan Huang, Shang Li, Liang Wang, Tieniu Tan

More importantly, \textit{Restorer} is trained with the kernel estimated by \textit{Estimator}, instead of the ground-truth kernel, thus \textit{Restorer} could be more tolerant to the estimation error of \textit{Estimator}.

Blind Super-Resolution Super-Resolution

Robust Face-Swap Detection Based on 3D Facial Shape Information

no code implementations28 Apr 2021 Weinan Guan, Wei Wang, Jing Dong, Bo Peng, Tieniu Tan

Maliciously-manipulated images or videos - so-called deep fakes - especially face-swap images and videos have attracted more and more malicious attackers to discredit some key figures.

SOGAN: 3D-Aware Shadow and Occlusion Robust GAN for Makeup Transfer

no code implementations21 Apr 2021 Yueming Lyu, Jing Dong, Bo Peng, Wei Wang, Tieniu Tan

Since human faces are symmetrical in the UV space, we can conveniently remove the undesired shadow and occlusion from the reference image by carefully designing a Flip Attention Module (FAM).

Face Model Facial Makeup Transfer

Graph Classification by Mixture of Diverse Experts

no code implementations29 Mar 2021 Fenyu Hu, Liping Wang, Shu Wu, Liang Wang, Tieniu Tan

Graph classification is a challenging research problem in many applications across a broad range of domains.

Classification General Classification +1

Focal and Efficient IOU Loss for Accurate Bounding Box Regression

no code implementations20 Jan 2021 Yi-Fan Zhang, Weiqiang Ren, Zhang Zhang, Zhen Jia, Liang Wang, Tieniu Tan

(ii) Most of the loss functions ignore the imbalance problem in BBR that the large number of anchor boxes which have small overlaps with the target boxes contribute most to the optimization of BBR.

object-detection Object Detection +1

Rethinking the Heatmap Regression for Bottom-up Human Pose Estimation

1 code implementation CVPR 2021 Zhengxiong Luo, Zhicheng Wang, Yan Huang, Tieniu Tan, Erjin Zhou

However, for bottom-up methods, which need to handle a large variance of human scales and labeling ambiguities, the current practice seems unreasonable.

Pose Estimation

Efficient Human Pose Estimation by Learning Deeply Aggregated Representations

no code implementations13 Dec 2020 Zhengxiong Luo, Zhicheng Wang, Yuanhao Cai, GuanAn Wang, Yan Huang, Liang Wang, Erjin Zhou, Tieniu Tan, Jian Sun

Instead, we focus on exploiting multi-scale information from layers with different receptive-field sizes and then making full of use this information by improving the fusion method.

Pose Estimation

Style Intervention: How to Achieve Spatial Disentanglement with Style-based Generators?

no code implementations19 Nov 2020 Yunfan Liu, Qi Li, Zhenan Sun, Tieniu Tan

Generative Adversarial Networks (GANs) with style-based generators (e. g. StyleGAN) successfully enable semantic control over image synthesis, and recent studies have also revealed that interpretable image translations could be obtained by modifying the latent code.

Disentanglement Image Generation +1

Unfolding the Alternating Optimization for Blind Super Resolution

1 code implementation NeurIPS 2020 Zhengxiong Luo, Yan Huang, Shang Li, Liang Wang, Tieniu Tan

More importantly, \textit{Restorer} is trained with the kernel estimated by \textit{Estimator}, instead of ground-truth kernel, thus \textit{Restorer} could be more tolerant to the estimation error of \textit{Estimator}.

Blind Super-Resolution Burst Image Super-Resolution +1

TFNet: Multi-Semantic Feature Interaction for CTR Prediction

no code implementations29 Jun 2020 Shu Wu, Feng Yu, Xueli Yu, Qiang Liu, Liang Wang, Tieniu Tan, Jie Shao, Fan Huang

The CTR (Click-Through Rate) prediction plays a central role in the domain of computational advertising and recommender systems.

Click-Through Rate Prediction Recommendation Systems

TAGNN: Target Attentive Graph Neural Networks for Session-based Recommendation

1 code implementation6 May 2020 Feng Yu, Yanqiao Zhu, Qiang Liu, Shu Wu, Liang Wang, Tieniu Tan

However, these methods compress a session into one fixed representation vector without considering the target items to be predicted.

Session-Based Recommendations

Cosmetic-Aware Makeup Cleanser

no code implementations20 Apr 2020 Yi Li, Huaibo Huang, Junchi Yu, Ran He, Tieniu Tan

Face verification aims at determining whether a pair of face images belongs to the same identity.

Face Parsing Face Verification +1

Learning Pose-invariant 3D Object Reconstruction from Single-view Images

1 code implementation3 Apr 2020 Bo Peng, Wei Wang, Jing Dong, Tieniu Tan

Learning to reconstruct 3D shapes using 2D images is an active research topic, with benefits of not requiring expensive 3D data.

3D Object Reconstruction Domain Adaptation

Temporal Sparse Adversarial Attack on Sequence-based Gait Recognition

no code implementations22 Feb 2020 Ziwen He, Wei Wang, Jing Dong, Tieniu Tan

In this paper, we demonstrate that the state-of-the-art gait recognition model is vulnerable to such attacks.

Adversarial Attack Gait Recognition

A New Ensemble Method for Concessively Targeted Multi-model Attack

no code implementations19 Dec 2019 Ziwen He, Wei Wang, Xinsheng Xuan, Jing Dong, Tieniu Tan

Thus, in this paper, we propose a new attack mechanism which performs the non-targeted attack when the targeted attack fails.

Image Classification

Dynamic Graph Representation for Partially Occluded Biometrics

1 code implementation1 Dec 2019 Min Ren, Yunlong Wang, Zhenan Sun, Tieniu Tan

During dynamic graph matching, we propose a novel strategy to measure the distances of both nodes and adjacent matrixes.

Graph Matching

A3GAN: An Attribute-aware Attentive Generative Adversarial Network for Face Aging

no code implementations15 Nov 2019 Yunfan Liu, Qi Li, Zhenan Sun, Tieniu Tan

Face aging, which aims at aesthetically rendering a given face to predict its future appearance, has received significant research attention in recent years.

GraphAIR: Graph Representation Learning with Neighborhood Aggregation and Interaction

1 code implementation5 Nov 2019 Fenyu Hu, Yanqiao Zhu, Shu Wu, Weiran Huang, Liang Wang, Tieniu Tan

Then, in order to better capture the complicated non-linearity of graph data, we present a novel GraphAIR framework which models the neighborhood interaction in addition to neighborhood aggregation.

Community Detection General Classification +3

Efficient Neural Architecture Transformation Searchin Channel-Level for Object Detection

no code implementations5 Sep 2019 Junran Peng, Ming Sun, Zhao-Xiang Zhang, Tieniu Tan, Junjie Yan

With the combination of these two designs, an architecture transformation scheme could be discovered to adapt a network designed for image classification to task of object detection.

Image Classification Neural Architecture Search +2

POD: Practical Object Detection with Scale-Sensitive Network

no code implementations ICCV 2019 Junran Peng, Ming Sun, Zhao-Xiang Zhang, Tieniu Tan, Junjie Yan

Scale-sensitive object detection remains a challenging task, where most of the existing methods could not learn it explicitly and are not robust to scale variance.

object-detection Object Detection

Progressive Cluster Purification for Transductive Few-shot Learning

no code implementations10 Jun 2019 Chenyang Si, Wentao Chen, Wei Wang, Liang Wang, Tieniu Tan

Furthermore, the inter-class classification and the intra-class transduction are extremely flexible to be repeated several times to progressively purify the clusters.

Few-Shot Learning General Classification

Fast Supervised Discrete Hashing

no code implementations7 Apr 2019 Jie Gui, Tongliang Liu, Zhenan Sun, DaCheng Tao, Tieniu Tan

Rather than adopting this method, FSDH uses a very simple yet effective regression of the class labels of training examples to the corresponding hash code to accelerate the algorithm.

Meta-SR: A Magnification-Arbitrary Network for Super-Resolution

2 code implementations CVPR 2019 Xuecai Hu, Haoyuan Mu, Xiangyu Zhang, Zilei Wang, Tieniu Tan, Jian Sun

In this work, we propose a novel method called Meta-SR to firstly solve super-resolution of arbitrary scale factor (including non-integer scale factors) with a single model.

Image Super-Resolution Single Image Super Resolution

Cross-spectral Face Completion for NIR-VIS Heterogeneous Face Recognition

no code implementations10 Feb 2019 Ran He, Jie Cao, Lingxiao Song, Zhenan Sun, Tieniu Tan

This paper models high resolution heterogeneous face synthesis as a complementary combination of two components, a texture inpainting component and pose correction component.

Face Generation Face Recognition +3

Session-based Recommendation with Graph Neural Networks

7 code implementations1 Nov 2018 Shu Wu, Yuyuan Tang, Yanqiao Zhu, Liang Wang, Xing Xie, Tieniu Tan

To obtain accurate item embedding and take complex transitions of items into account, we propose a novel method, i. e. Session-based Recommendation with Graph Neural Networks, SR-GNN for brevity.

Session-Based Recommendations

Pose-Guided Multi-Granularity Attention Network for Text-Based Person Search

no code implementations22 Sep 2018 Ya Jing, Chenyang Si, Jun-Bo Wang, Wei Wang, Liang Wang, Tieniu Tan

To exploit the multilevel corresponding visual contents, we propose a pose-guided multi-granularity attention network (PMA).

Person Search Text based Person Search

Accelerating Deep Neural Networks with Spatial Bottleneck Modules

no code implementations7 Sep 2018 Junran Peng, Lingxi Xie, Zhao-Xiang Zhang, Tieniu Tan, Jingdong Wang

This paper presents an efficient module named spatial bottleneck for accelerating the convolutional layers in deep neural networks.

End-to-end View Synthesis for Light Field Imaging with Pseudo 4DCNN

no code implementations ECCV 2018 Yunlong Wang, Fei Liu, Zilei Wang, Guangqi Hou, Zhenan Sun, Tieniu Tan

Limited angular resolution has become the main bottleneck of microlens-based plenoptic cameras towards practical vision applications.

Depth Estimation

IntroVAE: Introspective Variational Autoencoders for Photographic Image Synthesis

3 code implementations NeurIPS 2018 Huaibo Huang, Zhihang Li, Ran He, Zhenan Sun, Tieniu Tan

On the other hand, the inference model is encouraged to classify between the generated and real samples while the generator tries to fool it as GANs.

Image Generation

DeepFirearm: Learning Discriminative Feature Representation for Fine-grained Firearm Retrieval

1 code implementation8 Jun 2018 Jiedong Hao, Jing Dong, Wei Wang, Tieniu Tan

There are great demands for automatically regulating inappropriate appearance of shocking firearm images in social media or identifying firearm types in forensics.

Image Retrieval

Multistage Adversarial Losses for Pose-Based Human Image Synthesis

no code implementations CVPR 2018 Chenyang Si, Wei Wang, Liang Wang, Tieniu Tan

Human image synthesis has extensive practical applications e. g. person re-identification and data augmentation for human pose estimation.

Data Augmentation Image Generation +2

M3: Multimodal Memory Modelling for Video Captioning

no code implementations CVPR 2018 Junbo Wang, Wei Wang, Yan Huang, Liang Wang, Tieniu Tan

Inspired by the facts that memory modelling poses potential advantages to long-term sequential problems [35] and working memory is the key factor of visual attention [33], we propose a Multimodal Memory Model (M3) to describe videos, which builds a visual and textual shared memory to model the long-term visual-textual dependency and further guide visual attention on described visual targets to solve visual-textual alignments.

Computer Vision Video Captioning

Geometry Guided Adversarial Facial Expression Synthesis

no code implementations10 Dec 2017 Lingxiao Song, Zhihe Lu, Ran He, Zhenan Sun, Tieniu Tan

An expression invariant face recognition experiment is also performed to further show the advantages of our proposed method.

Face Recognition Face Transfer +1

Anti-Makeup: Learning A Bi-Level Adversarial Network for Makeup-Invariant Face Verification

no code implementations12 Sep 2017 Yi Li, Lingxiao Song, Xiang Wu, Ran He, Tieniu Tan

This paper proposes a learning from generation approach for makeup-invariant face verification by introducing a bi-level adversarial network (BLAN).

Face Verification

Wasserstein CNN: Learning Invariant Features for NIR-VIS Face Recognition

no code implementations8 Aug 2017 Ran He, Xiang Wu, Zhenan Sun, Tieniu Tan

To avoid the over-fitting problem on small-scale heterogeneous face data, a correlation prior is introduced on the fully-connected layers of WCNN network to reduce parameter space.

Face Recognition Heterogeneous Face Recognition

Deep Supervised Discrete Hashing

no code implementations NeurIPS 2017 Qi Li, Zhenan Sun, Ran He, Tieniu Tan

Benefit from recent advances in deep learning, deep hashing methods have achieved promising results for image retrieval.

General Classification Image Retrieval

Coupled Deep Learning for Heterogeneous Face Recognition

no code implementations8 Apr 2017 Xiang Wu, Lingxiao Song, Ran He, Tieniu Tan

CDL seeks a shared feature space in which the heterogeneous face matching problem can be approximately treated as a homogeneous face matching problem.

Face Recognition Heterogeneous Face Recognition

Multimodal Memory Modelling for Video Captioning

no code implementations17 Nov 2016 Junbo Wang, Wei Wang, Yan Huang, Liang Wang, Tieniu Tan

In this paper, we propose a Multimodal Memory Model (M3) to describe videos, which builds a visual and textual shared memory to model the long-term visual-textual dependency and further guide global visual attention on described targets.

Computer Vision Video Captioning

DeMeshNet: Blind Face Inpainting for Deep MeshFace Verification

no code implementations16 Nov 2016 Shu Zhang, Ran He, Tieniu Tan

The occlusions incurred by random meshes severely degenerate the performance of face verification systems, which raises the MeshFace verification problem between MeshFace and daily photos.

Face Alignment Face Verification +1

What Is the Best Practice for CNNs Applied to Visual Instance Retrieval?

1 code implementation5 Nov 2016 Jiedong Hao, Jing Dong, Wei Wang, Tieniu Tan

Based on the evaluation results, we also identify the best choices for different factors and propose a new multi-scale image feature representation method to encode the image effectively.

Image Retrieval

ICE: Information Credibility Evaluation on Social Media via Representation Learning

no code implementations29 Sep 2016 Qiang Liu, Shu Wu, Feng Yu, Liang Wang, Tieniu Tan

In this paper, we propose a novel representation learning method, Information Credibility Evaluation (ICE), to learn representations of information credibility on social media.

Feature Engineering Representation Learning

ReD-SFA: Relation Discovery Based Slow Feature Analysis for Trajectory Clustering

no code implementations CVPR 2016 Zhang Zhang, Kaiqi Huang, Tieniu Tan, Peipei Yang, Jun Li

For spectral embedding/clustering, it is still an open problem on how to construct an relation graph to reflect the intrinsic structures in data.

graph construction Motion Segmentation +2

A Light CNN for Deep Face Representation with Noisy Labels

7 code implementations9 Nov 2015 Xiang Wu, Ran He, Zhenan Sun, Tieniu Tan

This paper presents a Light CNN framework to learn a compact embedding on the large-scale face data with massive noisy labels.

Face Identification Face Recognition +2

Learning Structured Ordinal Measures for Video based Face Recognition

no code implementations9 Jul 2015 Ran He, Tieniu Tan, Larry Davis, Zhenan Sun

This paper presents a structured ordinal measure method for video-based face recognition that simultaneously learns ordinal filters and structured ordinal features.

Face Recognition

Relevance Topic Model for Unstructured Social Group Activity Recognition

no code implementations NeurIPS 2013 Fang Zhao, Yongzhen Huang, Liang Wang, Tieniu Tan

Unstructured social group activity recognition in web videos is a challenging task due to 1) the semantic gap between class labels and low-level visual features and 2) the lack of labeled training data.

Group Activity Recognition Variational Inference

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