b'Wei Shen'

research

∙ 07/06/2022

Unsupervised Domain Adaptation through Shape Modeling for Medical Image Segmentation

Shape information is a strong and valuable prior in segmenting organs in...

Yuan Yao, et al. ∙

research

∙ 07/04/2022

A Survey on Label-efficient Deep Segmentation: Bridging the Gap between Weak Supervision and Dense Prediction

The rapid development of deep learning has made a great progress in segm...

Wei Shen, et al. ∙

research

∙ 06/22/2022

Multi-View Clustering for Open Knowledge Base Canonicalization

Open information extraction (OIE) methods extract plenty of OIE triples ...

Wei Shen, et al. ∙

research

∙ 06/04/2022

Video-based Human-Object Interaction Detection from Tubelet Tokens

We present a novel vision Transformer, named TUTOR, which is able to lea...

Danyang Tu, et al. ∙

research

∙ 05/24/2022

Community Question Answering Entity Linking via Leveraging Auxiliary Data

Community Question Answering (CQA) platforms contain plenty of CQA texts...

Yuhan Li, et al. ∙

research

∙ 04/21/2022

ChildPredictor: A Child Face Prediction Framework with Disentangled Learning

The appearances of children are inherited from their parents, which make...

Yuzhi Zhao, et al. ∙

research

∙ 04/18/2022

Saliency in Augmented Reality

With the rapid development of multimedia technology, Augmented Reality (...

Huiyu Duan, et al. ∙

research

∙ 03/22/2022

CP2: Copy-Paste Contrastive Pretraining for Semantic Segmentation

Recent advances in self-supervised contrastive learning yield good image...

Feng Wang, et al. ∙

research

∙ 03/20/2022

Iwin: Human-Object Interaction Detection via Transformer with Irregular Windows

This paper presents a new vision Transformer, named Iwin Transformer, wh...

Danyang Tu, et al. ∙

research

∙ 03/20/2022

End-to-End Human-Gaze-Target Detection with Transformers

In this paper, we propose an effective and efficient method for Human-Ga...

Danyang Tu, et al. ∙

research

∙ 03/18/2022

ContrastMask: Contrastive Learning to Segment Every Thing

Partially-supervised instance segmentation is a task which requests segm...

Xuehui Wang, et al. ∙

research

∙ 01/04/2022

External Attention Assisted Multi-Phase Splenic Vascular Injury Segmentation with Limited Data

The spleen is one of the most commonly injured solid organs in blunt abd...

Yuyin Zhou, et al. ∙

research

∙ 11/23/2021

Deep Residual Fourier Transformation for Single Image Deblurring

It has been a common practice to adopt the ResBlock, which learns the di...

Xintian Mao, et al. ∙

research

∙ 11/15/2021

iBOT: Image BERT Pre-Training with Online Tokenizer

The success of language Transformers is primarily attributed to the pret...

Jinghao Zhou, et al. ∙

research

∙ 09/26/2021

Entity Linking Meets Deep Learning: Techniques and Solutions

Entity linking (EL) is the process of linking entity mentions appearing ...

Wei Shen, et al. ∙

research

∙ 08/25/2021

Inductive Matrix Completion Using Graph Autoencoder

Recently, the graph neural network (GNN) has shown great power in matrix...

Wei Shen, et al. ∙

research

∙ 06/24/2021

Bidding via Clustering Ads Intentions: an Efficient Search Engine Marketing System for E-commerce

With the increasing scale of search engine marketing, designing an effic...

Cheng Jie, et al. ∙

research

∙ 06/05/2021

Making CNNs Interpretable by Building Dynamic Sequential Decision Forests with Top-down Hierarchy Learning

In this paper, we propose a generic model transfer scheme to make Convlu...

Yilin Wang, et al. ∙

research

∙ 06/04/2021

Glance-and-Gaze Vision Transformer

Recently, there emerges a series of vision Transformers, which show supe...

Qihang Yu, et al. ∙

research

∙ 05/31/2021

Learning Inductive Attention Guidance for Partially Supervised Pancreatic Ductal Adenocarcinoma Prediction

Pancreatic ductal adenocarcinoma (PDAC) is the third most common cause o...

Yan Wang, et al. ∙

research

∙ 03/05/2021

SpecTr: Spectral Transformer for Hyperspectral Pathology Image Segmentation

Hyperspectral imaging (HSI) unlocks the huge potential to a wide variety...

Boxiang Yun, et al. ∙

research

∙ 11/28/2020

Batch Normalization with Enhanced Linear Transformation

Batch normalization (BN) is a fundamental unit in modern deep networks, ...

Yuhui Xu, et al. ∙

research

∙ 10/29/2020

Volumetric Medical Image Segmentation: A 3D Deep Coarse-to-fine Framework and Its Adversarial Examples

Although deep neural networks have been a dominant method for many 2D vi...

Yingwei Li, et al. ∙

research

∙ 10/14/2020

AutoADR: Automatic Model Design for Ad Relevance

Large-scale pre-trained models have attracted extensive attention in the...

Yiren Chen, et al. ∙

research

∙ 10/12/2020

Shape-Texture Debiased Neural Network Training

Shape and texture are two prominent and complementary cues for recognizi...

Yingwei Li, et al. ∙

research

∙ 10/05/2020

CO2: Consistent Contrast for Unsupervised Visual Representation Learning

Contrastive learning has been adopted as a core method for unsupervised ...

Chen Wei, et al. ∙

research

∙ 08/25/2020

Auxiliary-task Based Deep Reinforcement Learning for Participant Selection Problem in Mobile Crowdsourcing

In mobile crowdsourcing (MCS), the platform selects participants to comp...

Wei Shen, et al. ∙

research

∙ 07/09/2020

Towards Unsupervised Learning for Instrument Segmentation in Robotic Surgery with Cycle-Consistent Adversarial Networks

Surgical tool segmentation in endoscopic images is an important problem:...

Daniil Pakhomov, et al. ∙

research

∙ 05/18/2020

Domain Adaptive Relational Reasoning for 3D Multi-Organ Segmentation

In this paper, we present a novel unsupervised domain adaptation (UDA) m...

Shuhao Fu, et al. ∙

research

∙ 04/04/2020

Segmentation for Classification of Screening Pancreatic Neuroendocrine Tumors

This work presents comprehensive results to detect in the early stage th...

Zhuotun Zhu, et al. ∙

research

∙ 03/18/2020

Detecting Pancreatic Adenocarcinoma in Multi-phase CT Scans via Alignment Ensemble

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancer...

Yingda Xia, et al. ∙

research

∙ 03/18/2020

Synthesize then Compare: Detecting Failures and Anomalies for Semantic Segmentation

The ability to detect failures and anomalies are fundamental requirement...

Yingda Xia, et al. ∙

research

∙ 12/06/2019

Deep Distance Transform for Tubular Structure Segmentation in CT Scans

Tubular structure segmentation in medical images, e.g., segmenting vesse...

Yan Wang, et al. ∙

research

∙ 11/25/2019

Shape-aware Feature Extraction for Instance Segmentation

Modern instance segmentation approaches mainly adopt a sequential paradi...

Hao Ding, et al. ∙

research

∙ 11/21/2019

Rethinking Normalization and Elimination Singularity in Neural Networks

In this paper, we study normalization methods for neural networks from t...

Siyuan Qiao, et al. ∙

research

∙ 09/09/2019

TDAPNet: Prototype Network with Recurrent Top-Down Attention for Robust Object Classification under Partial Occlusion

Despite deep convolutional neural networks' great success in object clas...

Mingqing Xiao, et al. ∙

research

∙ 07/23/2019

Deep Differentiable Random Forests for Age Estimation

Age estimation from facial images is typically cast as a label distribut...

Wei Shen, et al. ∙

research

∙ 06/30/2019

Learning to Find Correlated Features by Maximizing Information Flow in Convolutional Neural Networks

Training convolutional neural networks for image classification tasks us...

Wei Shen, et al. ∙

research

∙ 04/25/2019

Stability and Optimization Error of Stochastic Gradient Descent for Pairwise Learning

In this paper we study the stability and its trade-off with optimization...

Wei Shen, et al. ∙

research

∙ 03/25/2019

Weight Standardization

In this paper, we propose Weight Standardization (WS) to accelerate deep...

Siyuan Qiao, et al. ∙

research

∙ 03/25/2019

Learning from Adversarial Features for Few-Shot Classification

Many recent few-shot learning methods concentrate on designing novel mod...

Wei Shen, et al. ∙

research

∙ 12/05/2018

Learning to generate filters for convolutional neural networks

Conventionally, convolutional neural networks (CNNs) process different i...

Wei Shen, et al. ∙

research

∙ 11/28/2018

Robust Face Detection via Learning Small Faces on Hard Images

Recent anchor-based deep face detectors have achieved promising performa...

Zhishuai Zhang, et al. ∙

research

∙ 11/27/2018

Tackling Early Sparse Gradients in Softmax Activation Using Leaky Squared Euclidean Distance

Softmax activation is commonly used to output the probability distributi...

Wei Shen, et al. ∙

research

∙ 11/27/2018

Generating Attention from Classifier Activations for Fine-grained Recognition

Recent advances in fine-grained recognition utilize attention maps to lo...

Wei Shen, et al. ∙

research

∙ 07/09/2018

PCL: Proposal Cluster Learning for Weakly Supervised Object Detection

Weakly Supervised Object Detection (WSOD), using only image-level annota...

Peng Tang, et al. ∙

research

∙ 05/16/2018

Spatial Transformer Introspective Neural Network

Natural images contain many variations such as illumination differences,...

Yunhan Zhao, et al. ∙

research

∙ 04/23/2018

Abdominal multi-organ segmentation with organ-attention networks and statistical fusion

Accurate and robust segmentation of abdominal organs on CT is essential ...

Yan Wang, et al. ∙

research

∙ 04/07/2018

Training Multi-organ Segmentation Networks with Sample Selection by Relaxed Upper Confident Bound

Deep convolutional neural networks (CNNs), especially fully convolutiona...

Yan Wang, et al. ∙

research

∙ 04/07/2018

Semi-supervised multi-organ segmentation via multi-planar co-training

Multi-organ segmentation is a critical problem in medical image analysis...

Yuyin Zhou, et al. ∙

Wei Shen

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