Search Results for author: Wei Shen

Found 93 papers, 33 papers with code

Enhancing Self-Attention with Knowledge-Assisted Attention Maps

no code implementations NAACL 2022 Jiangang Bai, Yujing Wang, Hong Sun, Ruonan Wu, Tianmeng Yang, Pengfei Tang, Defu Cao, Mingliang Zhang1, Yunhai Tong, Yaming Yang, Jing Bai, Ruofei Zhang, Hao Sun, Wei Shen

Large-scale pre-trained language models have attracted extensive attentions in the research community and shown promising results on various tasks of natural language processing.

Multi-Task Learning Natural Language Understanding

Finding Lookalike Customers for E-Commerce Marketing

no code implementations9 Jan 2023 Yang Peng, Changzheng Liu, Wei Shen

Customer-centric marketing campaigns generate a large portion of e-commerce website traffic for Walmart.

Marketing

MagicNet: Semi-Supervised Multi-Organ Segmentation via Magic-Cube Partition and Recovery

no code implementations29 Dec 2022 Duowen Chen, Yunhao Bai, Wei Shen, Qingli Li, Lequan Yu, Yan Wang

Our strategy encourages unlabeled images to learn organ semantics in relative locations from the labeled images (cross-branch) and enhances the learning ability for small organs (within-branch).

Anatomy Data Augmentation +3

TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets

1 code implementation5 Dec 2022 Yuanying Cai, Chuheng Zhang, Li Zhao, Wei Shen, Xuyun Zhang, Lei Song, Jiang Bian, Tao Qin, TieYan Liu

There are two challenges for this setting: 1) The optimal trade-off between optimizing the RL signal and the behavior cloning (BC) signal changes on different states due to the variation of the action coverage induced by different behavior policies.

D4RL Offline RL +2

A Transformer-Based User Satisfaction Prediction for Proactive Interaction Mechanism in DuerOS

no code implementations5 Dec 2022 Wei Shen, Xiaonan He, Chuheng Zhang, Xuyun Zhang, Jian Xie

Moreover, they are trained and evaluated on the benchmark datasets with adequate labels, which are expensive to obtain in a commercial dialogue system.

Spoken Dialogue Systems

Joint Open Knowledge Base Canonicalization and Linking

no code implementations Proceedings of the 2021 International Conference on Management of Data 2021 Yinan Liu, Wei Shen, Yuanfei Wang, Jianyong Wang, Zhenglu Yang, Xiaojie Yuan

However, noun phrases (NPs) and relation phrases (RPs) in OKBs are not canonicalized and often appear in different paraphrased textual variants, which leads to redundant and ambiguous facts.

Open Information Extraction

Low-resource Personal Attribute Prediction from Conversation

no code implementations28 Nov 2022 Yinan Liu, Hu Chen, Wei Shen, Jiaoyan Chen

Previous studies often rely on a relative number of resources such as labeled utterances and external data, yet the attribute knowledge embedded in unlabeled utterances is underutilized and their performance of predicting some difficult personal attributes is still unsatisfactory.

text-classification Text Classification

Self-supervised Character-to-Character Distillation

no code implementations1 Nov 2022 Tongkun Guan, Wei Shen

Although these methods employ large-scale synthetic text images to reduce the dependence on annotated real images, the domain gap limits the recognition performance.

Data Augmentation Representation Learning +2

Skeleton2Humanoid: Animating Simulated Characters for Physically-plausible Motion In-betweening

1 code implementation9 Oct 2022 Yunhao Li, Zhenbo Yu, Yucheng Zhu, Bingbing Ni, Guangtao Zhai, Wei Shen

Stage I introduces a test time adaptation strategy, which improves the physical plausibility of synthesized human skeleton motions by optimizing skeleton joint locations.

Motion Synthesis

TEDL: A Two-stage Evidential Deep Learning Method for Classification Uncertainty Quantification

no code implementations12 Sep 2022 Xue Li, Wei Shen, Denis Charles

In this paper, we propose TEDL, a two-stage learning approach to quantify uncertainty for deep learning models in classification tasks, inspired by our findings in experimenting with Evidential Deep Learning (EDL) method, a recently proposed uncertainty quantification approach based on the Dempster-Shafer theory.

SwiftPruner: Reinforced Evolutionary Pruning for Efficient Ad Relevance

no code implementations30 Aug 2022 Li Lyna Zhang, Youkow Homma, Yujing Wang, Min Wu, Mao Yang, Ruofei Zhang, Ting Cao, Wei Shen

Remarkably, under our latency requirement of 1900us on CPU, SwiftPruner achieves a 0. 86% higher AUC than the state-of-the-art uniform sparse baseline for BERT-Mini on a large scale real-world dataset.

Personal Attribute Prediction from Conversations

no code implementations29 Aug 2022 Yinan Liu, Hu Chen, Wei Shen

Personal knowledge bases (PKBs) are critical to many applications, such as Web-based chatbots and personalized recommendation.

Language Modelling

Learning Entity Linking Features for Emerging Entities

1 code implementation8 Aug 2022 Chenwei Ran, Wei Shen, Jianbo Gao, Yuhan Li, Jianyong Wang, Yantao Jia

Entity linking (EL) is the process of linking entity mentions appearing in text with their corresponding entities in a knowledge base.

Entity Linking

Unsupervised Domain Adaptation through Shape Modeling for Medical Image Segmentation

1 code implementation6 Jul 2022 Yuan YAO, Fengze Liu, Zongwei Zhou, Yan Wang, Wei Shen, Alan Yuille, Yongyi Lu

Previous methods proposed Variational Autoencoder (VAE) based models to learn the distribution of shape for a particular organ and used it to automatically evaluate the quality of a segmentation prediction by fitting it into the learned shape distribution.

Image Segmentation Pancreas Segmentation +2

Multi-View Clustering for Open Knowledge Base Canonicalization

1 code implementation22 Jun 2022 Wei Shen, Yang Yang, Yinan Liu

In this paper, we propose CMVC, a novel unsupervised framework that leverages these two views of knowledge jointly for canonicalizing OKBs without the need of manually annotated labels.

Open Information Extraction

Video-based Human-Object Interaction Detection from Tubelet Tokens

no code implementations4 Jun 2022 Danyang Tu, Wei Sun, Xiongkuo Min, Guangtao Zhai, Wei Shen

We present a novel vision Transformer, named TUTOR, which is able to learn tubelet tokens, served as highly-abstracted spatiotemporal representations, for video-based human-object interaction (V-HOI) detection.

Human-Object Interaction Detection

Community Question Answering Entity Linking via Leveraging Auxiliary Data

1 code implementation24 May 2022 Yuhan Li, Wei Shen, Jianbo Gao, Yadong Wang

Community Question Answering (CQA) platforms contain plenty of CQA texts (i. e., questions and answers corresponding to the question) where named entities appear ubiquitously.

Community Question Answering Entity Linking

ChildPredictor: A Child Face Prediction Framework with Disentangled Learning

1 code implementation21 Apr 2022 Yuzhi Zhao, Lai-Man Po, Xuehui Wang, Qiong Yan, Wei Shen, Yujia Zhang, Wei Liu, Chun-Kit Wong, Chiu-Sing Pang, Weifeng Ou, Wing-Yin Yu, Buhua Liu

On this basis, we formulate predictions as a mapping from parents' genetic factors to children's genetic factors, and disentangle them from external and variety factors.

Age-Invariant Face Recognition Image-to-Image Translation +1

Saliency in Augmented Reality

1 code implementation18 Apr 2022 Huiyu Duan, Wei Shen, Xiongkuo Min, Danyang Tu, Jing Li, Guangtao Zhai

Therefore, in this paper, we mainly analyze the interaction effect between background (BG) scenes and AR contents, and study the saliency prediction problem in AR.

Saliency Prediction

CP2: Copy-Paste Contrastive Pretraining for Semantic Segmentation

1 code implementation22 Mar 2022 Feng Wang, Huiyu Wang, Chen Wei, Alan Yuille, Wei Shen

Recent advances in self-supervised contrastive learning yield good image-level representation, which favors classification tasks but usually neglects pixel-level detailed information, leading to unsatisfactory transfer performance to dense prediction tasks such as semantic segmentation.

Contrastive Learning Representation Learning +1

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

no code implementations20 Mar 2022 Danyang Tu, Xiongkuo Min, Huiyu Duan, Guodong Guo, Guangtao Zhai, Wei Shen

Iwin Transformer is a hierarchical Transformer which progressively performs token representation learning and token agglomeration within irregular windows.

Human-Object Interaction Detection object-detection +3

ContrastMask: Contrastive Learning to Segment Every Thing

1 code implementation CVPR 2022 Xuehui Wang, Kai Zhao, Ruixin Zhang, Shouhong Ding, Yan Wang, Wei Shen

In this framework, annotated masks of seen categories and pseudo masks of unseen categories serve as a prior for contrastive learning, where features from the mask regions (foreground) are pulled together, and are contrasted against those from the background, and vice versa.

Instance Segmentation Semi-Supervised Instance Segmentation

Geometric Synthesis: A Free lunch for Large-scale Palmprint Recognition Model Pretraining

no code implementations11 Mar 2022 Kai Zhao, Lei Shen, Yingyi Zhang, Chuhan Zhou, Tao Wang, Ruixin Zhang, Shouhong Ding, Wei Jia, Wei Shen

In this paper, by observing that palmar creases are the key information to deep-learning-based palmprint recognition, we propose to synthesize training data by manipulating palmar creases.

Self-supervised Implicit Glyph Attention for Text Recognition

no code implementations7 Mar 2022 Tongkun Guan, Chaochen Gu, Jingzheng Tu, Xue Yang, Qi Feng, Yudi Zhao, Wei Shen

Supervised attention can alleviate the above issue, but it is category-specific, which requires extra laborious character-level bounding box annotations and would be memory-intensive when the number of character categories is large.

Scene Text Recognition Text Segmentation

Consensus Synergizes with Memory: A Simple Approach for Anomaly Segmentation in Urban Scenes

no code implementations24 Nov 2021 Jiazhong Cen, Zenkun Jiang, Lingxi Xie, Qi Tian, Xiaokang Yang, Wei Shen

Anomaly segmentation is a crucial task for safety-critical applications, such as autonomous driving in urban scenes, where the goal is to detect out-of-distribution (OOD) objects with categories which are unseen during training.

Anomaly Detection Autonomous Driving

Intriguing Findings of Frequency Selection for Image Deblurring

2 code implementations23 Nov 2021 Xintian Mao, Yiming Liu, Fengze Liu, Qingli Li, Wei Shen, Yan Wang

Blur was naturally analyzed in the frequency domain, by estimating the latent sharp image and the blur kernel given a blurry image.

Deblurring Image Deblurring +1

Image BERT Pre-training with Online Tokenizer

no code implementations ICLR 2022 Jinghao Zhou, Chen Wei, Huiyu Wang, Wei Shen, Cihang Xie, Alan Yuille, Tao Kong

The success of language Transformers is primarily attributed to the pretext task of masked language modeling (MLM), where texts are first tokenized into semantically meaningful pieces.

Image Classification Instance Segmentation +5

Entity Linking Meets Deep Learning: Techniques and Solutions

no code implementations26 Sep 2021 Wei Shen, Yuhan Li, Yinan Liu, Jiawei Han, Jianyong Wang, Xiaojie Yuan

Entity linking (EL) is the process of linking entity mentions appearing in web text with their corresponding entities in a knowledge base.

Entity Linking Knowledge Base Population +2

Inductive Matrix Completion Using Graph Autoencoder

2 code implementations25 Aug 2021 Wei Shen, Chuheng Zhang, Yun Tian, Liang Zeng, Xiaonan He, Wanchun Dou, Xiaolong Xu

However, without node content (i. e., side information) for training, the user (or item) specific representation can not be learned in the inductive setting, that is, a model trained on one group of users (or items) cannot adapt to new users (or items).

Matrix Completion Recommendation Systems

An Efficient Group-based Search Engine Marketing System for E-Commerce

no code implementations24 Jun 2021 Cheng Jie, Da Xu, Zigeng Wang, Lu Wang, Wei Shen

With the increasing scale of search engine marketing, designing an efficient bidding system is becoming paramount for the success of e-commerce companies.

Marketing

Dual Attention Guided Gaze Target Detection in the Wild

1 code implementation CVPR 2021 Yi Fang, Jiapeng Tang, Wang Shen, Wei Shen, Xiao Gu, Li Song, Guangtao Zhai

In the third stage, we use the generated dual attention as guidance to perform two sub-tasks: (1) identifying whether the gaze target is inside or out of the image; (2) locating the target if inside.

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

no code implementations5 Jun 2021 Yilin Wang, Shaozuo Yu, Xiaokang Yang, Wei Shen

In this paper, we propose a generic model transfer scheme to make Convlutional Neural Networks (CNNs) interpretable, while maintaining their high classification accuracy.

Classification

Glance-and-Gaze Vision Transformer

1 code implementation NeurIPS 2021 Qihang Yu, Yingda Xia, Yutong Bai, Yongyi Lu, Alan Yuille, Wei Shen

It is motivated by the Glance and Gaze behavior of human beings when recognizing objects in natural scenes, with the ability to efficiently model both long-range dependencies and local context.

Learning Inductive Attention Guidance for Partially Supervised Pancreatic Ductal Adenocarcinoma Prediction

no code implementations31 May 2021 Yan Wang, Peng Tang, Yuyin Zhou, Wei Shen, Elliot K. Fishman, Alan L. Yuille

We instantiate both the global and the local classifiers by multiple instance learning (MIL), where the attention guidance, indicating roughly where the PDAC regions are, is the key to bridging them: For global MIL based normal/PDAC classification, attention serves as a weight for each instance (voxel) during MIL pooling, which eliminates the distraction from the background; For local MIL based semi-supervised PDAC segmentation, the attention guidance is inductive, which not only provides bag-level pseudo-labels to training data without per-voxel annotations for MIL training, but also acts as a proxy of an instance-level classifier.

Multiple Instance Learning

Toward Tweet Entity Linking with Heterogeneous Information Networks

1 code implementation IEEE Transactions on Knowledge and Data Engineering 2021 Wei Shen, Yuwei Yin, Yang Yang, Jiawei Han, Jianyong Wang, Xiaojie Yuan

The task of linking an entity mention in a tweet with its corresponding entity in a heterogeneous information network is of great importance, for the purpose of enriching heterogeneous information networks with the abundant and fresh knowledge embedded in tweets.

Entity Linking Metric Learning

SpecTr: Spectral Transformer for Hyperspectral Pathology Image Segmentation

1 code implementation5 Mar 2021 Boxiang Yun, Yan Wang, Jieneng Chen, Huiyu Wang, Wei Shen, Qingli Li

Hyperspectral imaging (HSI) unlocks the huge potential to a wide variety of applications relied on high-precision pathology image segmentation, such as computational pathology and precision medicine.

Image Segmentation Semantic Segmentation

Looking Here or There? Gaze Following in 360-Degree Images

no code implementations ICCV 2021 Yunhao Li, Wei Shen, Zhongpai Gao, Yucheng Zhu, Guangtao Zhai, Guodong Guo

Specifically, the local region is obtained as a 2D cone-shaped field along the 2D projection of the sight line starting at the human subject's head position, and the distant region is obtained by searching along the sight line in 3D sphere space.

Batch Normalization with Enhanced Linear Transformation

1 code implementation28 Nov 2020 Yuhui Xu, Lingxi Xie, Cihang Xie, Jieru Mei, Siyuan Qiao, Wei Shen, Hongkai Xiong, Alan Yuille

Batch normalization (BN) is a fundamental unit in modern deep networks, in which a linear transformation module was designed for improving BN's flexibility of fitting complex data distributions.

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

no code implementations29 Oct 2020 Yingwei Li, Zhuotun Zhu, Yuyin Zhou, Yingda Xia, Wei Shen, Elliot K. Fishman, Alan L. Yuille

Although deep neural networks have been a dominant method for many 2D vision tasks, it is still challenging to apply them to 3D tasks, such as medical image segmentation, due to the limited amount of annotated 3D data and limited computational resources.

Image Segmentation Pancreas Segmentation +2

Shape-Texture Debiased Neural Network Training

1 code implementation ICLR 2021 Yingwei Li, Qihang Yu, Mingxing Tan, Jieru Mei, Peng Tang, Wei Shen, Alan Yuille, Cihang Xie

To prevent models from exclusively attending on a single cue in representation learning, we augment training data with images with conflicting shape and texture information (eg, an image of chimpanzee shape but with lemon texture) and, most importantly, provide the corresponding supervisions from shape and texture simultaneously.

Adversarial Robustness Data Augmentation +2

CO2: Consistent Contrast for Unsupervised Visual Representation Learning

no code implementations ICLR 2021 Chen Wei, Huiyu Wang, Wei Shen, Alan Yuille

Regarding the similarity of the query crop to each crop from other images as "unlabeled", the consistency term takes the corresponding similarity of a positive crop as a pseudo label, and encourages consistency between these two similarities.

Contrastive Learning Image Classification +5

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

no code implementations25 Aug 2020 Wei Shen, Xiaonan He, Chuheng Zhang, Qiang Ni, Wanchun Dou, Yan Wang

Therefore, it is crucial to design a participant selection algorithm that applies to different MCS systems to achieve multiple goals.

Combinatorial Optimization Fairness +2

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

no code implementations9 Jul 2020 Daniil Pakhomov, Wei Shen, Nassir Navab

Surgical tool segmentation in endoscopic images is an important problem: it is a crucial step towards full instrument pose estimation and it is used for integration of pre- and intra-operative images into the endoscopic view.

Image Segmentation Image-to-Image Translation +2

Domain Adaptive Relational Reasoning for 3D Multi-Organ Segmentation

no code implementations18 May 2020 Shuhao Fu, Yongyi Lu, Yan Wang, Yuyin Zhou, Wei Shen, Elliot Fishman, Alan Yuille

In this paper, we present a novel unsupervised domain adaptation (UDA) method, named Domain Adaptive Relational Reasoning (DARR), to generalize 3D multi-organ segmentation models to medical data collected from different scanners and/or protocols (domains).

Relational Reasoning Super-Resolution +1

Segmentation for Classification of Screening Pancreatic Neuroendocrine Tumors

no code implementations4 Apr 2020 Zhuotun Zhu, Yongyi Lu, Wei Shen, Elliot K. Fishman, Alan L. Yuille

This work presents comprehensive results to detect in the early stage the pancreatic neuroendocrine tumors (PNETs), a group of endocrine tumors arising in the pancreas, which are the second common type of pancreatic cancer, by checking the abdominal CT scans.

Classification General Classification +1

Synthesize then Compare: Detecting Failures and Anomalies for Semantic Segmentation

1 code implementation ECCV 2020 Yingda Xia, Yi Zhang, Fengze Liu, Wei Shen, Alan Yuille

The ability to detect failures and anomalies are fundamental requirements for building reliable systems for computer vision applications, especially safety-critical applications of semantic segmentation, such as autonomous driving and medical image analysis.

Ranked #5 on Anomaly Detection on Road Anomaly (using extra training data)

Anomaly Detection Autonomous Driving +2

Deep Distance Transform for Tubular Structure Segmentation in CT Scans

no code implementations CVPR 2020 Yan Wang, Xu Wei, Fengze Liu, Jieneng Chen, Yuyin Zhou, Wei Shen, Elliot K. Fishman, Alan L. Yuille

Tubular structure segmentation in medical images, e. g., segmenting vessels in CT scans, serves as a vital step in the use of computers to aid in screening early stages of related diseases.

Deeply Shape-guided Cascade for Instance Segmentation

1 code implementation CVPR 2021 Hao Ding, Siyuan Qiao, Alan Yuille, Wei Shen

The key to a successful cascade architecture for precise instance segmentation is to fully leverage the relationship between bounding box detection and mask segmentation across multiple stages.

Instance Segmentation Region Proposal +1

Rethinking Normalization and Elimination Singularity in Neural Networks

1 code implementation21 Nov 2019 Siyuan Qiao, Huiyu Wang, Chenxi Liu, Wei Shen, Alan Yuille

To address this issue, we propose BatchChannel Normalization (BCN), which uses batch knowledge to avoid the elimination singularities in the training of channel-normalized models.

Image Classification Instance Segmentation +3

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

no code implementations9 Sep 2019 Mingqing Xiao, Adam Kortylewski, Ruihai Wu, Siyuan Qiao, Wei Shen, Alan Yuille

Despite deep convolutional neural networks' great success in object classification, it suffers from severe generalization performance drop under occlusion due to the inconsistency between training and testing data.

General Classification Object Recognition

Deep Differentiable Random Forests for Age Estimation

no code implementations23 Jul 2019 Wei Shen, Yilu Guo, Yan Wang, Kai Zhao, Bo wang, Alan Yuille

Both of them connect split nodes to the top layer of convolutional neural networks (CNNs) and deal with inhomogeneous data by jointly learning input-dependent data partitions at the split nodes and age distributions at the leaf nodes.

Age Estimation regression

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

no code implementations30 Jun 2019 Wei Shen, Fei Li, Rujie Liu

We argue that the discard of the correlated discriminative information is partially caused by the fact that the minimization of the classification loss doesn't ensure to learn the overall discriminative information but only the most discriminative information.

Classification General Classification +1

Stability and Optimization Error of Stochastic Gradient Descent for Pairwise Learning

no code implementations25 Apr 2019 Wei Shen, Zhenhuan Yang, Yiming Ying, Xiaoming Yuan

From this fundamental trade-off, we obtain lower bounds for the optimization error of SGD algorithms and the excess expected risk over a class of pairwise losses.

Generalization Bounds Metric Learning

Learning from Adversarial Features for Few-Shot Classification

no code implementations25 Mar 2019 Wei Shen, Ziqiang Shi, Jun Sun

Then we use the adversarial region attention to aggregate the feature maps to obtain the adversarial features.

Classification Few-Shot Learning +1

Learning to generate filters for convolutional neural networks

no code implementations ICLR 2018 Wei Shen, Rujie Liu

In this paper, we propose to generate sample-specific filters for convolutional layers in the forward pass.

Robust Face Detection via Learning Small Faces on Hard Images

1 code implementation28 Nov 2018 Zhishuai Zhang, Wei Shen, Siyuan Qiao, Yan Wang, Bo wang, Alan Yuille

In this paper, we propose that the robustness of a face detector against hard faces can be improved by learning small faces on hard images.

Face Detection

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

no code implementations27 Nov 2018 Wei Shen, Rujie Liu

However, we find that choosing squared Euclidean distance may cause distance explosion leading gradients to be extremely sparse in the early stage of back propagation.

One-Shot Learning

Generating Attention from Classifier Activations for Fine-grained Recognition

no code implementations27 Nov 2018 Wei Shen, Rujie Liu

Recent advances in fine-grained recognition utilize attention maps to localize objects of interest.

Semantic Segmentation

PCL: Proposal Cluster Learning for Weakly Supervised Object Detection

4 code implementations9 Jul 2018 Peng Tang, Xinggang Wang, Song Bai, Wei Shen, Xiang Bai, Wenyu Liu, Alan Yuille

The iterative instance classifier refinement is implemented online using multiple streams in convolutional neural networks, where the first is an MIL network and the others are for instance classifier refinement supervised by the preceding one.

Multiple Instance Learning object-detection +2

Hifi: Hierarchical feature integration for skeleton detection

no code implementations1 Jul 2018 Kai Zhao, Wei Shen, ShangHua Gao, Dandan Li, Ming-Ming Cheng

In natural images, the scales (thickness) of object skeletons may dramatically vary among objects and object parts.

Object Skeleton Detection

Resisting Large Data Variations via Introspective Transformation Network

no code implementations16 May 2018 Yunhan Zhao, Ye Tian, Charless Fowlkes, Wei Shen, Alan Yuille

Experimental results verify that our approach significantly improves the ability of deep networks to resist large variations between training and testing data and achieves classification accuracy improvements on several benchmark datasets, including MNIST, affNIST, SVHN, CIFAR-10 and miniImageNet.

Data Augmentation Few-Shot Learning

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

no code implementations23 Apr 2018 Yan Wang, Yuyin Zhou, Wei Shen, Seyoun Park, Elliot K. Fishman, Alan L. Yuille

To address these challenges, we introduce a novel framework for multi-organ segmentation by using organ-attention networks with reverse connections (OAN-RCs) which are applied to 2D views, of the 3D CT volume, and output estimates which are combined by statistical fusion exploiting structural similarity.

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

no code implementations7 Apr 2018 Yan Wang, Yuyin Zhou, Peng Tang, Wei Shen, Elliot K. Fishman, Alan L. Yuille

Based on the fact that very hard samples might have annotation errors, we propose a new sample selection policy, named Relaxed Upper Confident Bound (RUCB).

Image Segmentation Medical Image Segmentation +1

Semi-Supervised Multi-Organ Segmentation via Deep Multi-Planar Co-Training

no code implementations7 Apr 2018 Yuyin Zhou, Yan Wang, Peng Tang, Song Bai, Wei Shen, Elliot K. Fishman, Alan L. Yuille

In multi-organ segmentation of abdominal CT scans, most existing fully supervised deep learning algorithms require lots of voxel-wise annotations, which are usually difficult, expensive, and slow to obtain.

Image Segmentation Semantic Segmentation

Deep Co-Training for Semi-Supervised Image Recognition

1 code implementation ECCV 2018 Siyuan Qiao, Wei Shen, Zhishuai Zhang, Bo wang, Alan Yuille

We present Deep Co-Training, a deep learning based method inspired by the Co-Training framework.

Hi-Fi: Hierarchical Feature Integration for Skeleton Detection

no code implementations5 Jan 2018 Kai Zhao, Wei Shen, Shang-Hua Gao, Dandan Li, Ming-Ming Cheng

In natural images, the scales (thickness) of object skeletons may dramatically vary among objects and object parts, making object skeleton detection a challenging problem.

Object Skeleton Detection

Single-Shot Object Detection with Enriched Semantics

no code implementations CVPR 2018 Zhishuai Zhang, Siyuan Qiao, Cihang Xie, Wei Shen, Bo wang, Alan L. Yuille

Our motivation is to enrich the semantics of object detection features within a typical deep detector, by a semantic segmentation branch and a global activation module.

object-detection Object Detection +1

Gradually Updated Neural Networks for Large-Scale Image Recognition

no code implementations ICML 2018 Siyuan Qiao, Zhishuai Zhang, Wei Shen, Bo wang, Alan Yuille

Our method is by introducing computation orderings to the channels within convolutional layers or blocks, based on which we gradually compute the outputs in a channel-wise manner.

ScaleNet: Guiding Object Proposal Generation in Supermarkets and Beyond

no code implementations ICCV 2017 Siyuan Qiao, Wei Shen, Weichao Qiu, Chenxi Liu, Alan Yuille

We argue that estimation of object scales in images is helpful for generating object proposals, especially for supermarket images where object scales are usually within a small range.

Object Proposal Generation

Multi-stage Multi-recursive-input Fully Convolutional Networks for Neuronal Boundary Detection

no code implementations ICCV 2017 Wei Shen, Bin Wang, Yuan Jiang, Yan Wang, Alan Yuille

This design is biologically-plausible, as it likes a human visual system to compare different possible segmentation solutions to address the ambiguous boundary issue.

Boundary Detection

Label Distribution Learning Forests

no code implementations NeurIPS 2017 Wei Shen, Kai Zhao, Yilu Guo, Alan Yuille

This paper presents label distribution learning forests (LDLFs) - a novel label distribution learning algorithm based on differentiable decision trees, which have several advantages: 1) Decision trees have the potential to model any general form of label distributions by a mixture of leaf node predictions.

Representation Learning

A Fixed-Point Model for Pancreas Segmentation in Abdominal CT Scans

3 code implementations25 Dec 2016 Yuyin Zhou, Lingxi Xie, Wei Shen, Yan Wang, Elliot K. Fishman, Alan L. Yuille

Deep neural networks have been widely adopted for automatic organ segmentation from abdominal CT scans.

Pancreas Segmentation

Learning Residual Images for Face Attribute Manipulation

1 code implementation CVPR 2017 Wei Shen, Rujie Liu

The transformation networks are responsible for the attribute manipulation and its dual operation and the discriminative network is used to distinguish the generated images from real images.

DeepSkeleton: Learning Multi-task Scale-associated Deep Side Outputs for Object Skeleton Extraction in Natural Images

1 code implementation13 Sep 2016 Wei Shen, Kai Zhao, Yuan Jiang, Yan Wang, Xiang Bai, Alan Yuille

By observing the relationship between the receptive field sizes of the different layers in the network and the skeleton scales they can capture, we introduce two scale-associated side outputs to each stage of the network.

Multi-Task Learning object-detection +2

Shape Recognition by Bag of Skeleton-associated Contour Parts

no code implementations20 May 2016 Wei Shen, Yuan Jiang, Wenjing Gao, Dan Zeng, Xinggang Wang

Contour and skeleton are two complementary representations for shape recognition.

Association

Object Skeleton Extraction in Natural Images by Fusing Scale-associated Deep Side Outputs

no code implementations CVPR 2016 Wei Shen, Kai Zhao, Yuan Jiang, Yan Wang, Zhijiang Zhang, Xiang Bai

Object skeleton is a useful cue for object detection, complementary to the object contour, as it provides a structural representation to describe the relationship among object parts.

object-detection Object Detection

Symmetry-Based Text Line Detection in Natural Scenes

no code implementations CVPR 2015 Zheng Zhang, Wei Shen, Cong Yao, Xiang Bai

Recently, a variety of real-world applications have triggered huge demand for techniques that can extract textual information from natural scenes.

Line Detection Scene Text Detection

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