Search Results for author: Ya zhang

Found 74 papers, 17 papers with code

FTL: A universal framework for training low-bit DNNs via Feature Transfer

no code implementations ECCV 2020 Kunyuan Du, Ya zhang, Haibing Guan, Qi Tian, Shenggan Cheng, James Lin

Compared with low-bit models trained directly, the proposed framework brings 0. 5% to 3. 4% accuracy gains to three different quantization schemes.

Quantization Transfer Learning

Multiscale Spatio-Temporal Graph Neural Networks for 3D Skeleton-Based Motion Prediction

no code implementations25 Aug 2021 Maosen Li, Siheng Chen, Yangheng Zhao, Ya zhang, Yanfeng Wang, Qi Tian

The core of MST-GNN is a multiscale spatio-temporal graph that explicitly models the relations in motions at various spatial and temporal scales.

motion prediction

CaT: Weakly Supervised Object Detection with Category Transfer

no code implementations17 Aug 2021 Tianyue Cao, Lianyu Du, Xiaoyun Zhang, Siheng Chen, Ya zhang, Yan-Feng Wang

To handle overlapping category transfer, we propose a double-supervision mean teacher to gather common category information and bridge the domain gap between two datasets.

Object Classification Transfer Learning +1

Cooperative Learning for Noisy Supervision

no code implementations11 Aug 2021 Hao Wu, Jiangchao Yao, Ya zhang, Yanfeng Wang

Learning with noisy labels has gained the enormous interest in the robust deep learning area.

Learning with noisy labels

MS-KD: Multi-Organ Segmentation with Multiple Binary-Labeled Datasets

no code implementations5 Aug 2021 Shixiang Feng, YuHang Zhou, Xiaoman Zhang, Ya zhang, Yanfeng Wang

A novel Multi-teacher Single-student Knowledge Distillation (MS-KD) framework is proposed, where the teacher models are pre-trained single-organ segmentation networks, and the student model is a multi-organ segmentation network.

Knowledge Distillation

Online Multi-Agent Forecasting with Interpretable Collaborative Graph Neural Network

no code implementations2 Jul 2021 Maosen Li, Siheng Chen, Yanning Shen, Genjia Liu, Ivor W. Tsang, Ya zhang

This paper considers predicting future statuses of multiple agents in an online fashion by exploiting dynamic interactions in the system.

Human motion prediction motion prediction

Knowledge distillation from multi-modal to mono-modal segmentation networks

no code implementations17 Jun 2021 Minhao Hu, Matthis Maillard, Ya zhang, Tommaso Ciceri, Giammarco La Barbera, Isabelle Bloch, Pietro Gori

In this paper, we propose KD-Net, a framework to transfer knowledge from a trained multi-modal network (teacher) to a mono-modal one (student).

Brain Tumor Segmentation Knowledge Distillation +1

A Fourier-based Framework for Domain Generalization

1 code implementation CVPR 2021 Qinwei Xu, Ruipeng Zhang, Ya zhang, Yanfeng Wang, Qi Tian

Modern deep neural networks suffer from performance degradation when evaluated on testing data under different distributions from training data.

Data Augmentation Domain Generalization

Contrastive Attraction and Contrastive Repulsion for Representation Learning

no code implementations8 May 2021 Huangjie Zheng, Xu Chen, Jiangchao Yao, Hongxia Yang, Chunyuan Li, Ya zhang, Hao Zhang, Ivor Tsang, Jingren Zhou, Mingyuan Zhou

Extensive large-scale experiments on standard vision tasks show that CACR not only consistently outperforms existing CL methods on benchmark datasets in representation learning, but also provides interpretable contrastive weights, demonstrating the efficacy of the proposed doubly contrastive strategy.

Contrastive Learning Representation Learning

Monitoring urban ecosystem service value using dynamic multi-level grids

no code implementations15 Apr 2021 Zhenfeng Shao, Yong Li, Xiao Huang, Bowen Cai, Lin Ding, Wenkang Pan, Ya zhang

Ecosystem valuation is a method of assigning a monetary value to an ecosystem with its goods and services, often referred to as ecosystem service value (ESV).

Adaptive Mutual Supervision for Weakly-Supervised Temporal Action Localization

no code implementations6 Apr 2021 Chen Ju, Peisen Zhao, Siheng Chen, Ya zhang, Xiaoyun Zhang, Qi Tian

To solve this issue, we introduce an adaptive mutual supervision framework (AMS) with two branches, where the base branch adopts CAS to localize the most discriminative action regions, while the supplementary branch localizes the less discriminative action regions through a novel adaptive sampler.

Weakly Supervised Action Localization Weakly-supervised Temporal Action Localization +1

Collaborative Label Correction via Entropy Thresholding

no code implementations31 Mar 2021 Hao Wu, Jiangchao Yao, Jiajie Wang, Yinru Chen, Ya zhang, Yanfeng Wang

Deep neural networks (DNNs) have the capacity to fit extremely noisy labels nonetheless they tend to learn data with clean labels first and then memorize those with noisy labels.

Spatio-Temporal Sparsification for General Robust Graph Convolution Networks

no code implementations23 Mar 2021 Mingming Lu, Ya zhang

Graph Neural Networks (GNNs) have attracted increasing attention due to its successful applications on various graph-structure data.

Sequential Learning on Liver Tumor Boundary Semantics and Prognostic Biomarker Mining

no code implementations9 Mar 2021 Jieneng Chen, Ke Yan, Yu-Dong Zhang, YouBao Tang, Xun Xu, Shuwen Sun, Qiuping Liu, Lingyun Huang, Jing Xiao, Alan L. Yuille, Ya zhang, Le Lu

(2) The sampled deep vertex features with positional embedding are mapped into a sequential space and decoded by a multilayer perceptron (MLP) for semantic classification.

Uncertainty-aware Incremental Learning for Multi-organ Segmentation

no code implementations9 Mar 2021 YuHang Zhou, Xiaoman Zhang, Shixiang Feng, Ya zhang, Yanfeng

Specifically, given a pretrained $K$ organ segmentation model and a new single-organ dataset, we train a unified $K+1$ organ segmentation model without accessing any data belonging to the previous training stages.

Incremental Learning Transfer Learning

Invariant Teacher and Equivariant Student for Unsupervised 3D Human Pose Estimation

1 code implementation17 Dec 2020 Chenxin Xu, Siheng Chen, Maosen Li, Ya zhang

To handle the decomposition ambiguity in the teacher network, we propose a cycle-consistent architecture promoting a 3D rotation-invariant property to train the teacher network.

3D Human Pose Estimation Knowledge Distillation +1

Point-Level Temporal Action Localization: Bridging Fully-supervised Proposals to Weakly-supervised Losses

no code implementations15 Dec 2020 Chen Ju, Peisen Zhao, Ya zhang, Yanfeng Wang, Qi Tian

Point-Level temporal action localization (PTAL) aims to localize actions in untrimmed videos with only one timestamp annotation for each action instance.

Weakly Supervised Action Localization

Deep Unsupervised Image Anomaly Detection: An Information Theoretic Framework

no code implementations9 Dec 2020 Fei Ye, Huangjie Zheng, Chaoqin Huang, Ya zhang

Based on this object function we introduce a novel information theoretic framework for unsupervised image anomaly detection.

Anomaly Detection

ESAD: End-to-end Deep Semi-supervised Anomaly Detection

no code implementations9 Dec 2020 Chaoqin Huang, Fei Ye, Ya zhang, Yan-Feng Wang, Qi Tian

This paper explores semi-supervised anomaly detection, a more practical setting for anomaly detection where a small additional set of labeled samples are provided.

Anomaly Detection Medical Diagnosis +1

Privileged Knowledge Distillation for Online Action Detection

no code implementations18 Nov 2020 Peisen Zhao, Lingxi Xie, Ya zhang, Yanfeng Wang, Qi Tian

Knowledge distillation is employed to transfer the privileged information from the offline teacher to the online student.

Action Detection Curriculum Learning +1

Sampling and Recovery of Graph Signals based on Graph Neural Networks

no code implementations3 Nov 2020 Siheng Chen, Maosen Li, Ya zhang

Compared to previous analytical sampling and recovery, the proposed methods are able to flexibly learn a variety of graph signal models from data by leveraging the learning ability of neural networks; compared to previous neural-network-based sampling and recovery, the proposed methods are designed through exploiting specific graph properties and provide interpretability.

Graph Classification

Learning on Attribute-Missing Graphs

2 code implementations3 Nov 2020 Xu Chen, Siheng Chen, Jiangchao Yao, Huangjie Zheng, Ya zhang, Ivor W Tsang

Thereby, designing a new GNN for these graphs is a burning issue to the graph learning community.

Graph Learning Link Prediction

Two-Stream Compare and Contrast Network for Vertebral Compression Fracture Diagnosis

no code implementations13 Oct 2020 Shixiang Feng, Beibei Liu, Ya zhang, Xiaoyun Zhang, Yuehua Li

In this paper, we explore to model VCFs diagnosis as a three-class classification problem, i. e. normal vertebrae, benign VCFs, and malignant VCFs.

Classification General Classification

SAR: Scale-Aware Restoration Learning for 3D Tumor Segmentation

no code implementations13 Oct 2020 Xiaoman Zhang, Shixiang Feng, YuHang Zhou, Ya zhang, Yanfeng Wang

We demonstrate the effectiveness of our methods on two downstream tasks: i) Brain tumor segmentation, ii) Pancreas tumor segmentation.

Brain Tumor Segmentation Self-Supervised Learning +2

Graph Cross Networks with Vertex Infomax Pooling

1 code implementation NeurIPS 2020 Maosen Li, Siheng Chen, Ya zhang, Ivor W. Tsang

Based on trainable hierarchical representations of a graph, GXN enables the interchange of intermediate features across scales to promote information flow.

Classification General Classification +1

Urban Traffic Flow Forecast Based on FastGCRNN

no code implementations17 Sep 2020 Ya Zhang, Mingming Lu, Haifeng Li

Traffic forecasting is an important prerequisite for the application of intelligent transportation systems in urban traffic networks.

Towards Equivalent Transformation of User Preferences in Cross Domain Recommendation

1 code implementation15 Sep 2020 Xu Chen, Ya zhang, Ivor Tsang, Yuangang Pan, Jingchao Su

The majority of recent methods have explored shared-user representation to transfer knowledge across different domains.

Recommendation Systems

Decoupled Variational Embedding for Signed Directed Networks

1 code implementation28 Aug 2020 Xu Chen, Jiangchao Yao, Maosen Li, Ya zhang, Yan-Feng Wang

Comprehensive results on both link sign prediction and node recommendation task demonstrate the effectiveness of DVE.

Link Sign Prediction Node Classification +1

Learning Robust Node Representations on Graphs

no code implementations26 Aug 2020 Xu Chen, Ya zhang, Ivor Tsang, Yuangang Pan

Graph neural networks (GNN), as a popular methodology for node representation learning on graphs, currently mainly focus on preserving the smoothness and identifiability of node representations.

Contrastive Learning Representation Learning

Collaborative Adversarial Learning for RelationalLearning on Multiple Bipartite Graphs

no code implementations16 Jul 2020 Jingchao Su, Xu Chen, Ya zhang, Siheng Chen, Dan Lv, Chenyang Li

The two-level alignment acts as two different constraints on different relations of the shared entities and facilitates better knowledge transfer for relational learning on multiple bipartite graphs.

Relational Reasoning Transfer Learning

Universal-to-Specific Framework for Complex Action Recognition

no code implementations13 Jul 2020 Peisen Zhao, Lingxi Xie, Ya zhang, Qi Tian

The U2S framework is composed of three subnetworks: a universal network, a category-specific network, and a mask network.

Action Recognition Decision Making

From Quantized DNNs to Quantizable DNNs

no code implementations11 Apr 2020 Kunyuan Du, Ya zhang, Haibing Guan

This paper proposes Quantizable DNNs, a special type of DNNs that can flexibly quantize its bit-width (denoted as `bit modes' thereafter) during execution without further re-training.

Dynamic Multiscale Graph Neural Networks for 3D Skeleton-Based Human Motion Prediction

1 code implementation17 Mar 2020 Maosen Li, Siheng Chen, Yangheng Zhao, Ya zhang, Yan-Feng Wang, Qi Tian

The core idea of DMGNN is to use a multiscale graph to comprehensively model the internal relations of a human body for motion feature learning.

3D Human Pose Estimation 3D Pose Estimation +2

Bottom-Up Temporal Action Localization with Mutual Regularization

1 code implementation ECCV 2020 Peisen Zhao, Lingxi Xie, Chen Ju, Ya zhang, Yan-Feng Wang, Qi Tian

To alleviate this problem, we introduce two regularization terms to mutually regularize the learning procedure: the Intra-phase Consistency (IntraC) regularization is proposed to make the predictions verified inside each phase; and the Inter-phase Consistency (InterC) regularization is proposed to keep consistency between these phases.

Temporal Action Localization

Attribute Restoration Framework for Anomaly Detection

1 code implementation25 Nov 2019 Chaoqin Huang, Fei Ye, Jinkun Cao, Maosen Li, Ya zhang, Cewu Lu

We here propose to break this equivalence by erasing selected attributes from the original data and reformulate it as a restoration task, where the normal and the anomalous data are expected to be distinguishable based on restoration errors.

Anomaly Detection

Cascading: Association Augmented Sequential Recommendation

no code implementations17 Oct 2019 Xu Chen, Kenan Cui, Ya zhang, Yan-Feng Wang

Recently, recommendation according to sequential user behaviors has shown promising results in many application scenarios.

Graph Embedding

Data Augmentation Revisited: Rethinking the Distribution Gap between Clean and Augmented Data

no code implementations19 Sep 2019 Zhuoxun He, Lingxi Xie, Xin Chen, Ya zhang, Yan-Feng Wang, Qi Tian

Data augmentation has been widely applied as an effective methodology to improve generalization in particular when training deep neural networks.

Data Augmentation Image Classification +1

Node Attribute Generation on Graphs

2 code implementations23 Jul 2019 Xu Chen, Siheng Chen, Huangjie Zheng, Jiangchao Yao, Kenan Cui, Ya zhang, Ivor W. Tsang

NANG learns a unifying latent representation which is shared by both node attributes and graph structures and can be translated to different modalities.

Data Augmentation General Classification +2

Defending Adversarial Attacks by Correcting logits

no code implementations26 Jun 2019 Yifeng Li, Lingxi Xie, Ya zhang, Rui Zhang, Yanfeng Wang, Qi Tian

Generating and eliminating adversarial examples has been an intriguing topic in the field of deep learning.

Handwritten Chinese Font Generation with Collaborative Stroke Refinement

no code implementations30 Apr 2019 Chuan Wen, Jie Chang, Ya zhang, Siheng Chen, Yan-Feng Wang, Mei Han, Qi Tian

Automatic character generation is an appealing solution for new typeface design, especially for Chinese typefaces including over 3700 most commonly-used characters.

Font Generation

Safeguarded Dynamic Label Regression for Generalized Noisy Supervision

1 code implementation6 Mar 2019 Jiangchao Yao, Ya zhang, Ivor W. Tsang, Jun Sun

We further generalize LCCN for open-set noisy labels and the semi-supervised setting.

Ranked #22 on Image Classification on Clothing1M (using extra training data)

Learning with noisy labels

Accelerate CNN via Recursive Bayesian Pruning

no code implementations ICCV 2019 Yuefu Zhou, Ya zhang, Yan-Feng Wang, Qi Tian

A new dropout-based measurement of redundancy, which facilitate the computation of posterior assuming inter-layer dependency, is introduced.

Domain-Invariant Adversarial Learning for Unsupervised Domain Adaption

no code implementations30 Nov 2018 Yexun Zhang, Ya zhang, Yan-Feng Wang, Qi Tian

Unsupervised domain adaption aims to learn a powerful classifier for the target domain given a labeled source data set and an unlabeled target data set.

Domain Adaptation

Phase Collaborative Network for Two-Phase Medical Image Segmentation

no code implementations28 Nov 2018 Huangjie Zheng, Lingxi Xie, Tianwei Ni, Ya zhang, Yan-Feng Wang, Qi Tian, Elliot K. Fishman, Alan L. Yuille

However, in medical image analysis, fusing prediction from two phases is often difficult, because (i) there is a domain gap between two phases, and (ii) the semantic labels are not pixel-wise corresponded even for images scanned from the same patient.

Medical Image Segmentation

Variational Collaborative Learning for User Probabilistic Representation

no code implementations22 Sep 2018 Kenan Cui, Xu Chen, Jiangchao Yao, Ya zhang

Conventional CF-based methods use the user-item interaction data as the sole information source to recommend items to users.

Recommendation Systems

Learning Multi-touch Conversion Attribution with Dual-attention Mechanisms for Online Advertising

1 code implementation11 Aug 2018 Kan Ren, Yuchen Fang, Wei-Nan Zhang, Shuhao Liu, Jiajun Li, Ya zhang, Yong Yu, Jun Wang

To achieve this, we utilize sequence-to-sequence prediction for user clicks, and combine both post-view and post-click attribution patterns together for the final conversion estimation.

Understanding VAEs in Fisher-Shannon Plane

no code implementations10 Jul 2018 Huangjie Zheng, Jiangchao Yao, Ya zhang, Ivor W. Tsang, Jia Wang

In information theory, Fisher information and Shannon information (entropy) are respectively used to quantify the uncertainty associated with the distribution modeling and the uncertainty in specifying the outcome of given variables.

Representation Learning

A Unified Framework for Generalizable Style Transfer: Style and Content Separation

1 code implementation13 Jun 2018 Yexun Zhang, Ya zhang, Wenbin Cai

The encoders are expected to capture the underlying features for different styles and contents which is generalizable to new styles and contents.

Multi-Task Learning Style Transfer

Webpage Saliency Prediction with Two-stage Generative Adversarial Networks

no code implementations29 May 2018 Yu Li, Ya zhang

Web page saliency prediction is a challenge problem in image transformation and computer vision.

Saliency Prediction

Masking: A New Perspective of Noisy Supervision

2 code implementations NeurIPS 2018 Bo Han, Jiangchao Yao, Gang Niu, Mingyuan Zhou, Ivor Tsang, Ya zhang, Masashi Sugiyama

It is important to learn various types of classifiers given training data with noisy labels.

Ranked #28 on Image Classification on Clothing1M (using extra training data)

Image Classification

Variational Composite Autoencoders

no code implementations12 Apr 2018 Jiangchao Yao, Ivor Tsang, Ya zhang

Learning in the latent variable model is challenging in the presence of the complex data structure or the intractable latent variable.

Multi-Scale Spatially-Asymmetric Recalibration for Image Classification

no code implementations ECCV 2018 Yan Wang, Lingxi Xie, Siyuan Qiao, Ya zhang, Wenjun Zhang, Alan L. Yuille

Convolution is spatially-symmetric, i. e., the visual features are independent of its position in the image, which limits its ability to utilize contextual cues for visual recognition.

Classification General Classification +1

Degeneration in VAE: in the Light of Fisher Information Loss

no code implementations19 Feb 2018 Huangjie Zheng, Jiangchao Yao, Ya zhang, Ivor W. Tsang

While enormous progress has been made to Variational Autoencoder (VAE) in recent years, similar to other deep networks, VAE with deep networks suffers from the problem of degeneration, which seriously weakens the correlation between the input and the corresponding latent codes, deviating from the goal of the representation learning.

Representation Learning

Collaborative Learning for Weakly Supervised Object Detection

no code implementations10 Feb 2018 Jiajie Wang, Jiangchao Yao, Ya zhang, Rui Zhang

For object detection, taking WSDDN-like architecture as weakly supervised detector sub-network and Faster-RCNN-like architecture as strongly supervised detector sub-network, we propose an end-to-end Weakly Supervised Collaborative Detection Network.

Weakly Supervised Object Detection

Separating Style and Content for Generalized Style Transfer

1 code implementation CVPR 2018 Yexun Zhang, Ya zhang, Wenbin Cai, Jie Chang

We here attempt to separate the representations for styles and contents, and propose a generalized style transfer network consisting of style encoder, content encoder, mixer and decoder.

Multi-Task Learning Style Transfer

Chinese Typeface Transformation with Hierarchical Adversarial Network

no code implementations17 Nov 2017 Jie Chang, Yujun Gu, Ya zhang

Inspired by the recent advancement in Generative Adversarial Networks (GANs), we propose a Hierarchical Adversarial Network (HAN) for typeface transformation.

Hierarchical structure Image Generation +1

Deep Learning from Noisy Image Labels with Quality Embedding

no code implementations2 Nov 2017 Jiangchao Yao, Jiajie Wang, Ivor Tsang, Ya zhang, Jun Sun, Chengqi Zhang, Rui Zhang

However, the label noise among the datasets severely degenerates the \mbox{performance of deep} learning approaches.

Query-free Clothing Retrieval via Implicit Relevance Feedback

no code implementations1 Nov 2017 Zhuoxiang Chen, Zhe Xu, Ya zhang, Xiao Gu

We model this problem as a new type of image retrieval task in which the target image resides only in the user's mind (called "mental image retrieval" hereafter).

Decision Making Image Retrieval

Deep Hashing with Triplet Quantization Loss

no code implementations31 Oct 2017 Yuefu Zhou, Shanshan Huang, Ya zhang, Yan-Feng Wang

While minimizing the quantization loss guarantees that quantization has minimal effect on retrieval accuracy, it unfortunately significantly reduces the expressiveness of features even before the quantization.

Image Retrieval Quantization

Clothing Retrieval with Visual Attention Model

no code implementations31 Oct 2017 Zhonghao Wang, Yujun Gu, Ya zhang, Jun Zhou, Xiao Gu

The VAM is further connected to a global network to form an end-to-end network structure through Impdrop connection which randomly Dropout on the feature maps with the probabilities given by the attention map.

SORT: Second-Order Response Transform for Visual Recognition

no code implementations ICCV 2017 Yan Wang, Lingxi Xie, Chenxi Liu, Ya zhang, Wenjun Zhang, Alan Yuille

In this paper, we reveal the importance and benefits of introducing second-order operations into deep neural networks.

Deep Collaborative Learning for Visual Recognition

no code implementations3 Mar 2017 Yan Wang, Lingxi Xie, Ya zhang, Wenjun Zhang, Alan Yuille

We formulate the function of a convolutional layer as learning a large visual vocabulary, and propose an alternative way, namely Deep Collaborative Learning (DCL), to reduce the computational complexity.

General Classification Image Classification

Unsupervised Triplet Hashing for Fast Image Retrieval

no code implementations28 Feb 2017 Shanshan Huang, Yichao Xiong, Ya zhang, Jia Wang

Considering the difficulty in obtaining labeled datasets for image retrieval task in large scale, we propose a novel CNN-based unsupervised hashing method, namely Unsupervised Triplet Hashing (UTH).

Image Retrieval Quantization

Part-Stacked CNN for Fine-Grained Visual Categorization

no code implementations CVPR 2016 Shaoli Huang, Zhe Xu, DaCheng Tao, Ya zhang

In the context of fine-grained visual categorization, the ability to interpret models as human-understandable visual manuals is sometimes as important as achieving high classification accuracy.

Classification Fine-Grained Image Classification +2

Augmenting Strong Supervision Using Web Data for Fine-Grained Categorization

no code implementations ICCV 2015 Zhe Xu, Shaoli Huang, Ya zhang, DaCheng Tao

We propose a new method for fine-grained object recognition that employs part-level annotations and deep convolutional neural networks (CNNs) in a unified framework.

Object Recognition

Multi-Touch Attribution in Online Advertising with Survival Theory

no code implementations 2014 IEEE International Conference on Data Mining 2015 Ya Zhang, Yi Wei, Jianbiao Ren

With the ever enhanced capability to tracking advertisement and users' interaction with the advertisement, data-driven multi-touch attribution models, which attempt to infer the contribution from user interaction data, become an important research direction.

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