Search Results for author: Zhongfei Zhang

Found 52 papers, 13 papers with code

BERT-enhanced Relational Sentence Ordering Network

no code implementations EMNLP 2020 Baiyun Cui, Yingming Li, Zhongfei Zhang

In this paper, we introduce a novel BERT-enhanced Relational Sentence Ordering Network (referred to as BRSON) by leveraging BERT for capturing better dependency relationship among sentences to enhance the coherence modeling for the entire paragraph.

Sentence Sentence Ordering

Dense Affinity Matching for Few-Shot Segmentation

no code implementations17 Jul 2023 Hao Chen, Yonghan Dong, Zheming Lu, Yunlong Yu, Yingming Li, Jungong Han, Zhongfei Zhang

Few-Shot Segmentation (FSS) aims to segment the novel class images with a few annotated samples.

Few-Shot Semantic Segmentation

Multi-Content Interaction Network for Few-Shot Segmentation

no code implementations11 Mar 2023 Hao Chen, Yunlong Yu, Yonghan Dong, Zheming Lu, Yingming Li, Zhongfei Zhang

Few-Shot Segmentation (FSS) is challenging for limited support images and large intra-class appearance discrepancies.

Reducing Flipping Errors in Deep Neural Networks

1 code implementation16 Mar 2022 Xiang Deng, Yun Xiao, Bo Long, Zhongfei Zhang

Deep neural networks (DNNs) have been widely applied in various domains in artificial intelligence including computer vision and natural language processing.

Test unseen

Deep Hybrid Models for Out-of-Distribution Detection

no code implementations CVPR 2022 Senqi Cao, Zhongfei Zhang

We propose a principled and practical method for out-of-distribution (OoD) detection with deep hybrid models (DHMs), which model the joint density p(x, y) of features and labels with a single forward pass.

Out-of-Distribution Detection Out of Distribution (OOD) Detection

Comprehensive Knowledge Distillation with Causal Intervention

1 code implementation NeurIPS 2021 Xiang Deng, Zhongfei Zhang

Knowledge distillation (KD) addresses model compression by distilling knowledge from a large model (teacher) to a smaller one (student).

Causal Inference Knowledge Distillation +2

Stable Prediction on Graphs with Agnostic Distribution Shift

no code implementations8 Oct 2021 Shengyu Zhang, Kun Kuang, Jiezhong Qiu, Jin Yu, Zhou Zhao, Hongxia Yang, Zhongfei Zhang, Fei Wu

The results demonstrate that our method outperforms various SOTA GNNs for stable prediction on graphs with agnostic distribution shift, including shift caused by node labels and attributes.

Graph Learning Recommendation Systems +1

Self-Taught Cross-Domain Few-Shot Learning with Weakly Supervised Object Localization and Task-Decomposition

no code implementations3 Sep 2021 Xiyao Liu, Zhong Ji, Yanwei Pang, Zhongfei Zhang

However, the target domain is absolutely unknown during the training on the source domain, which results in lacking directed guidance for target tasks.

cross-domain few-shot learning Weakly-Supervised Object Localization

Complementary Calibration: Boosting General Continual Learning with Collaborative Distillation and Self-Supervision

1 code implementation3 Sep 2021 Zhong Ji, Jin Li, Qiang Wang, Zhongfei Zhang

Furthermore, we explore a collaborative self-supervision idea to leverage pretext tasks and supervised contrastive learning for addressing the feature deviation problem by learning complete and discriminative features for all classes.

Continual Learning Contrastive Learning +2

Graph-Free Knowledge Distillation for Graph Neural Networks

1 code implementation16 May 2021 Xiang Deng, Zhongfei Zhang

In this paper, we propose to our best knowledge the first dedicated approach to distilling knowledge from a GNN without graph data.

Knowledge Distillation Transfer Learning

Can Students Outperform Teachers in Knowledge Distillation based Model Compression?

no code implementations1 Jan 2021 Xiang Deng, Zhongfei Zhang

By designing exploratory experiments, we find that model capacity differences are not necessarily the root reason, and the distillation data matters when the student capacity is greater than a threshold.

Knowledge Distillation Model Compression +1

Learning with Retrospection

3 code implementations24 Dec 2020 Xiang Deng, Zhongfei Zhang

Deep neural networks have been successfully deployed in various domains of artificial intelligence, including computer vision and natural language processing.

Deep Metric Learning with Spherical Embedding

no code implementations NeurIPS 2020 Dingyi Zhang, Yingming Li, Zhongfei Zhang

Deep metric learning has attracted much attention in recent years, due to seamlessly combining the distance metric learning and deep neural network.

Face Recognition Metric Learning +1

Sparsity-Control Ternary Weight Networks

no code implementations1 Nov 2020 Xiang Deng, Zhongfei Zhang

However, the existing approaches to training ternary weight networks cannot control the sparsity (i. e., percentage of 0s) of the ternary weights, which undermines the advantage of ternary weights.

SBAT: Video Captioning with Sparse Boundary-Aware Transformer

no code implementations23 Jul 2020 Tao Jin, Siyu Huang, Ming Chen, Yingming Li, Zhongfei Zhang

However, video captioning is a multimodal learning problem, and the video features have much redundancy between different time steps.

Machine Translation Text Generation +2

Multitask Non-Autoregressive Model for Human Motion Prediction

no code implementations13 Jul 2020 Bin Li, Jian Tian, Zhongfei Zhang, Hailin Feng, Xi Li

Human motion prediction, which aims at predicting future human skeletons given the past ones, is a typical sequence-to-sequence problem.

Action Recognition Human motion prediction +2

Is the Meta-Learning Idea Able to Improve the Generalization of Deep Neural Networks on the Standard Supervised Learning?

no code implementations27 Feb 2020 Xiang Deng, Zhongfei Zhang

In this paper, we propose a novel meta-learning based training procedure (MLTP) for DNNs and demonstrate that the meta-learning idea can indeed improve the generalization abilities of DNNs.

Few-Shot Learning

Fine-tune BERT with Sparse Self-Attention Mechanism

no code implementations IJCNLP 2019 Baiyun Cui, Yingming Li, Ming Chen, Zhongfei Zhang

In this paper, we develop a novel Sparse Self-Attention Fine-tuning model (referred as SSAF) which integrates sparsity into self-attention mechanism to enhance the fine-tuning performance of BERT.

Natural Language Inference Question Answering +1

Episode-based Prototype Generating Network for Zero-Shot Learning

1 code implementation CVPR 2020 Yunlong Yu, Zhong Ji, Zhongfei Zhang, Jungong Han

We introduce a simple yet effective episode-based training framework for zero-shot learning (ZSL), where the learning system requires to recognize unseen classes given only the corresponding class semantics.

Test Zero-Shot Learning

A Semantics-Guided Class Imbalance Learning Model for Zero-Shot Classification

no code implementations26 Aug 2019 Zhong Ji, Xuejie Yu, Yunlong Yu, Yanwei Pang, Zhongfei Zhang

Towards alleviating the class imbalance issue in ZSC, we propose a sample-balanced training process to encourage all training classes to contribute equally to the learned model.

General Classification Image Classification +2

Text Guided Person Image Synthesis

no code implementations CVPR 2019 Xingran Zhou, Siyu Huang, Bin Li, Yingming Li, Jiachen Li, Zhongfei Zhang

This paper presents a novel method to manipulate the visual appearance (pose and attribute) of a person image according to natural language descriptions.

Attribute Image Generation +1

Cross-relation Cross-bag Attention for Distantly-supervised Relation Extraction

1 code implementation27 Dec 2018 Yujin Yuan, Liyuan Liu, Siliang Tang, Zhongfei Zhang, Yueting Zhuang, ShiLiang Pu, Fei Wu, Xiang Ren

Distant supervision leverages knowledge bases to automatically label instances, thus allowing us to train relation extractor without human annotations.

Relation Relation Extraction +1

Perceiving Physical Equation by Observing Visual Scenarios

no code implementations29 Nov 2018 Siyu Huang, Zhi-Qi Cheng, Xi Li, Xiao Wu, Zhongfei Zhang, Alexander Hauptmann

To tackle this challenge, we present a novel pipeline comprised of an Observer Engine and a Physicist Engine by respectively imitating the actions of an observer and a physicist in the real world.

Bi-Adversarial Auto-Encoder for Zero-Shot Learning

no code implementations20 Nov 2018 Yunlong Yu, Zhong Ji, Yanwei Pang, Jichang Guo, Zhongfei Zhang, Fei Wu

Existing generative Zero-Shot Learning (ZSL) methods only consider the unidirectional alignment from the class semantics to the visual features while ignoring the alignment from the visual features to the class semantics, which fails to construct the visual-semantic interactions well.

Zero-Shot Learning

Deep Attentive Sentence Ordering Network

no code implementations EMNLP 2018 Baiyun Cui, Yingming Li, Ming Chen, Zhongfei Zhang

In this paper, we propose a novel deep attentive sentence ordering network (referred as ATTOrderNet) which integrates self-attention mechanism with LSTMs in the encoding of input sentences.

Concept-To-Text Generation Document Summarization +5

Stacked Pooling: Improving Crowd Counting by Boosting Scale Invariance

1 code implementation22 Aug 2018 Siyu Huang, Xi Li, Zhi-Qi Cheng, Zhongfei Zhang, Alexander Hauptmann

In this work, we explore the cross-scale similarity in crowd counting scenario, in which the regions of different scales often exhibit high visual similarity.

Crowd Counting Density Estimation

Partially Shared Multi-Task Convolutional Neural Network With Local Constraint for Face Attribute Learning

no code implementations CVPR 2018 Jiajiong Cao, Yingming Li, Zhongfei Zhang

Consequently, we present a local constraint regularized multi-task network, called Partially Shared Multi-task Convolutional Neural Network with Local Constraint (PS-MCNN-LC), where PS structure and local constraint are integrated together to help the framework learn better attribute representations.


Stacked Semantic-Guided Attention Model for Fine-Grained Zero-Shot Learning

no code implementations21 May 2018 Yunlong Yu, Zhong Ji, Yanwei Fu, Jichang Guo, Yanwei Pang, Zhongfei Zhang

To this end, we propose a novel stacked semantics-guided attention (S2GA) model to obtain semantic relevant features by using individual class semantic features to progressively guide the visual features to generate an attention map for weighting the importance of different local regions.

General Classification Multi-class Classification +2

GNAS: A Greedy Neural Architecture Search Method for Multi-Attribute Learning

no code implementations19 Apr 2018 Siyu Huang, Xi Li, Zhi-Qi Cheng, Zhongfei Zhang, Alexander Hauptmann

A key problem in deep multi-attribute learning is to effectively discover the inter-attribute correlation structures.

Attribute Neural Architecture Search

Pyramid Person Matching Network for Person Re-identification

no code implementations7 Mar 2018 Chaojie Mao, Yingming Li, Zhongfei Zhang, Yaqing Zhang, Xi Li

In this work, we present a deep convolutional pyramid person matching network (PPMN) with specially designed Pyramid Matching Module to address the problem of person re-identification.

Person Re-Identification

Multi-Channel Pyramid Person Matching Network for Person Re-Identification

no code implementations7 Mar 2018 Chaojie Mao, Yingming Li, Yaqing Zhang, Zhongfei Zhang, Xi Li

In particular, we learn separate deep representations for semantic-components and color-texture distributions from two person images and then employ pyramid person matching network (PPMN) to obtain correspondence representations.

Person Re-Identification

A Deep Learning Approach for Expert Identification in Question Answering Communities

no code implementations14 Nov 2017 Chen Zheng, Shuangfei Zhai, Zhongfei Zhang

This approach uses the convolutional neural network and combines user feature representations with question feature representations to compute scores that the user who gets the highest score is the expert on this question.

Question Answering Sentence

Text Coherence Analysis Based on Deep Neural Network

1 code implementation21 Oct 2017 Baiyun Cui, Yingming Li, Yaqing Zhang, Zhongfei Zhang

In this paper, we propose a novel deep coherence model (DCM) using a convolutional neural network architecture to capture the text coherence.

Sentence Sentence Ordering

Transductive Zero-Shot Learning with a Self-training dictionary approach

no code implementations27 Mar 2017 Yunlong Yu, Zhong Ji, Xi Li, Jichang Guo, Zhongfei Zhang, Haibin Ling, Fei Wu

As an important and challenging problem in computer vision, zero-shot learning (ZSL) aims at automatically recognizing the instances from unseen object classes without training data.

Transductive Learning Transfer Learning +1

Structural Correspondence Learning for Cross-lingual Sentiment Classification with One-to-many Mappings

no code implementations26 Nov 2016 Nana Li, Shuangfei Zhai, Zhongfei Zhang, Boying Liu

For simplicity, however, it assumes that the word translation oracle maps each pivot feature in source language to exactly only one word in target language.

Cross-Lingual Sentiment Classification General Classification +4

S3Pool: Pooling with Stochastic Spatial Sampling

4 code implementations CVPR 2017 Shuangfei Zhai, Hui Wu, Abhishek Kumar, Yu Cheng, Yongxi Lu, Zhongfei Zhang, Rogerio Feris

We view the pooling operation in CNNs as a two-step procedure: first, a pooling window (e. g., $2\times 2$) slides over the feature map with stride one which leaves the spatial resolution intact, and second, downsampling is performed by selecting one pixel from each non-overlapping pooling window in an often uniform and deterministic (e. g., top-left) manner.

Data Augmentation Image Classification

Generative Adversarial Networks as Variational Training of Energy Based Models

1 code implementation6 Nov 2016 Shuangfei Zhai, Yu Cheng, Rogerio Feris, Zhongfei Zhang

We propose VGAN, which works by minimizing a variational lower bound of the negative log likelihood (NLL) of an energy based model (EBM), where the model density $p(\mathbf{x})$ is approximated by a variational distribution $q(\mathbf{x})$ that is easy to sample from.

Doubly Convolutional Neural Networks

no code implementations NeurIPS 2016 Shuangfei Zhai, Yu Cheng, Weining Lu, Zhongfei Zhang

Building large models with parameter sharing accounts for most of the success of deep convolutional neural networks (CNNs).

Image Classification

A Survey of Multi-View Representation Learning

no code implementations3 Oct 2016 Yingming Li, Ming Yang, Zhongfei Zhang

Consequently, we first review the representative methods and theories of multi-view representation learning based on the perspective of alignment, such as correlation-based alignment.

Representation Learning

Zero-Shot Learning with Multi-Battery Factor Analysis

no code implementations30 Jun 2016 Zhong Ji, Yuzhong Xie, Yanwei Pang, Lei Chen, Zhongfei Zhang

Zero-shot learning (ZSL) extends the conventional image classification technique to a more challenging situation where the test image categories are not seen in the training samples.

Image Classification Test +1

Deep Structured Energy Based Models for Anomaly Detection

2 code implementations25 May 2016 Shuangfei Zhai, Yu Cheng, Weining Lu, Zhongfei Zhang

In this paper, we attack the anomaly detection problem by directly modeling the data distribution with deep architectures.

Anomaly Detection

Deep Learning Driven Visual Path Prediction from a Single Image

no code implementations27 Jan 2016 Siyu Huang, Xi Li, Zhongfei Zhang, Zhouzhou He, Fei Wu, Wei Liu, Jinhui Tang, Yueting Zhuang

The highly effective visual representation and deep context models ensure that our framework makes a deep semantic understanding of the scene and motion pattern, consequently improving the performance of the visual path prediction task.

Semisupervised Autoencoder for Sentiment Analysis

no code implementations14 Dec 2015 Shuangfei Zhai, Zhongfei Zhang

In this paper, we investigate the usage of autoencoders in modeling textual data.

Sentiment Analysis

Dropout Training of Matrix Factorization and Autoencoder for Link Prediction in Sparse Graphs

no code implementations14 Dec 2015 Shuangfei Zhai, Zhongfei Zhang

Matrix factorization (MF) and Autoencoder (AE) are among the most successful approaches of unsupervised learning.

Link Prediction Multiview Learning

Manifold Regularized Discriminative Neural Networks

no code implementations19 Nov 2015 Shuangfei Zhai, Zhongfei Zhang

The first one, named Label-Aware Manifold Regularization, assumes the availability of labels and penalizes large norms of the loss function w. r. t.

Multimodal Skip-gram Using Convolutional Pseudowords

no code implementations12 Nov 2015 Zachary Seymour, Yingming Li, Zhongfei Zhang

This work studies the representational mapping across multimodal data such that given a piece of the raw data in one modality the corresponding semantic description in terms of the raw data in another modality is immediately obtained.

Object Recognition Retrieval +2

Online Metric-Weighted Linear Representations for Robust Visual Tracking

no code implementations21 Jul 2015 Xi Li, Chunhua Shen, Anthony Dick, Zhongfei Zhang, Yueting Zhuang

Object identification results for an entire video sequence are achieved by systematically combining the tracking information and visual recognition at each frame.

Metric Learning Object +2

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