Search Results for author: Meng Yang

Found 29 papers, 7 papers with code

Semi-supervised Semantic Segmentation via Strong-weak Dual-branch Network

no code implementations ECCV 2020 Wenfeng Luo, Meng Yang

To fully explore the potential of the weak labels, we propose to impose separate treatments of strong and weak annotations via a strong-weak dual-branch network, which discriminates the massive inaccurate weak supervisions from those strong ones.

Segmentation Semi-Supervised Semantic Segmentation +2

Ultrasound Nodule Segmentation Using Asymmetric Learning with Simple Clinical Annotation

no code implementations23 Apr 2024 Xingyue Zhao, Zhongyu Li, Xiangde Luo, Peiqi Li, Peng Huang, Jianwei Zhu, Yang Liu, Jihua Zhu, Meng Yang, Shi Chang, Jun Dong

Especially, an asymmetric learning framework is developed by extending the aspect ratio annotations with two types of pseudo labels, i. e., conservative labels and radical labels, to train two asymmetric segmentation networks simultaneously.

Anatomy Morphological Analysis +1

CTC Blank Triggered Dynamic Layer-Skipping for Efficient CTC-based Speech Recognition

no code implementations4 Jan 2024 JunFeng Hou, Peiyao Wang, Jincheng Zhang, Meng Yang, Minwei Feng, Jingcheng Yin

Deploying end-to-end speech recognition models with limited computing resources remains challenging, despite their impressive performance.

Knowledge Distillation speech-recognition +1

G2-MonoDepth: A General Framework of Generalized Depth Inference from Monocular RGB+X Data

1 code implementation24 Oct 2023 Haotian Wang, Meng Yang, Nanning Zheng

This paper investigates a unified task of monocular depth inference, which infers high-quality depth maps from all kinds of input raw data from various robots in unseen scenes.

Data Augmentation Depth Completion +1

Asymmetric Co-Training with Explainable Cell Graph Ensembling for Histopathological Image Classification

no code implementations24 Aug 2023 Ziqi Yang, Zhongyu Li, Chen Liu, Xiangde Luo, Xingguang Wang, Dou Xu, CHAOQUN LI, Xiaoying Qin, Meng Yang, Long Jin

To make full use of pixel-level and cell-level features dynamically, we propose an asymmetric co-training framework combining a deep graph convolutional network and a convolutional neural network for multi-class histopathological image classification.

Classification Histopathological Image Classification +1

FS-Depth: Focal-and-Scale Depth Estimation from a Single Image in Unseen Indoor Scene

no code implementations27 Jul 2023 Chengrui Wei, Meng Yang, Lei He, Nanning Zheng

It has long been an ill-posed problem to predict absolute depth maps from single images in real (unseen) indoor scenes.

3D Reconstruction Data Augmentation +1

Fourier Transformer: Fast Long Range Modeling by Removing Sequence Redundancy with FFT Operator

1 code implementation24 May 2023 Ziwei He, Meng Yang, Minwei Feng, Jingcheng Yin, Xinbing Wang, Jingwen Leng, Zhouhan Lin

Many researchers have focused on designing new forms of self-attention or introducing new parameters to overcome this limitation, however a large portion of them prohibits the model to inherit weights from large pretrained models.

Abstractive Text Summarization Document Summarization +2

Semi-Supervised Few-Shot Learning via Multi-Factor Clustering

1 code implementation CVPR 2022 Jie Ling, Lei Liao, Meng Yang, Jia Shuai

And we exploit the pseudo labels of unlabeled samples by MFC to expand the support set for obtaining more distribution information.

Clustering Data Augmentation +2

Unsupervised Domain Adaptation for the Histopathological Cell Segmentation through Self-Ensembling

no code implementations MICCAI Workshop COMPAY 2021 CHAOQUN LI, Yitian Zhou, TangQi Shi, Yenan Wu, Meng Yang, Zhongyu Li

Meanwhile, we present a self-ensembling model to consider the source and the target domain together as a semi-supervised segmentation task to reduce the differences of outputs.

Cell Segmentation Segmentation +1

Leaning Compact and Representative Features for Cross-Modality Person Re-Identification

1 code implementation26 Mar 2021 Guangwei Gao, Hao Shao, Fei Wu, Meng Yang, Yi Yu

This paper pays close attention to the cross-modality visible-infrared person re-identification (VI Re-ID) task, which aims to match pedestrian samples between visible and infrared modes.

Cross-Modality Person Re-identification Knowledge Distillation +1

Hierarchical Deep CNN Feature Set-Based Representation Learning for Robust Cross-Resolution Face Recognition

no code implementations25 Mar 2021 Guangwei Gao, Yi Yu, Jian Yang, Guo-Jun Qi, Meng Yang

(i) To learn more robust and discriminative features, we desire to adaptively fuse the contextual features from different layers.

Face Recognition Representation Learning

Integrating Pre-trained Model into Rule-based Dialogue Management

no code implementations17 Feb 2021 Jun Quan, Meng Yang, Qiang Gan, Deyi Xiong, Yiming Liu, Yuchen Dong, Fangxin Ouyang, Jun Tian, Ruiling Deng, Yongzhi Li, Yang Yang, Daxin Jiang

Rule-based dialogue management is still the most popular solution for industrial task-oriented dialogue systems for their interpretablility.

Dialogue Management Management +1

HpGAN: Sequence Search with Generative Adversarial Networks

no code implementations10 Dec 2020 Mingxing Zhang, Zhengchun Zhou, Lanping Li, Zilong Liu, Meng Yang, Yanghe Feng

Sequences play an important role in many engineering applications and systems.

Pedestrian re-identification based on Tree branch network with local and global learning

no code implementations31 Mar 2019 Hui Li, Meng Yang, Zhihui Lai, Wei-Shi Zheng, Zitong Yu

Deep part-based methods in recent literature have revealed the great potential of learning local part-level representation for pedestrian image in the task of person re-identification.

Person Re-Identification

Toward Characteristic-Preserving Image-based Virtual Try-On Network

5 code implementations ECCV 2018 Bochao Wang, Huabin Zheng, Xiaodan Liang, Yimin Chen, Liang Lin, Meng Yang

Second, to alleviate boundary artifacts of warped clothes and make the results more realistic, we employ a Try-On Module that learns a composition mask to integrate the warped clothes and the rendered image to ensure smoothness.

Geometric Matching Virtual Try-on

An MM Algorithm for Split Feasibility Problems

no code implementations16 Dec 2016 Jason Xu, Eric C. Chi, Meng Yang, Kenneth Lange

Furthermore, we show that the Euclidean norm appearing in the proximity function of the non-linear split feasibility problem can be replaced by arbitrary Bregman divergences.

Large-Margin Softmax Loss for Convolutional Neural Networks

2 code implementations7 Dec 2016 Weiyang Liu, Yandong Wen, Zhiding Yu, Meng Yang

Cross-entropy loss together with softmax is arguably one of the most common used supervision components in convolutional neural networks (CNNs).

General Classification

Robust Elastic Net Regression

no code implementations15 Nov 2015 Weiyang Liu, Rongmei Lin, Meng Yang

We propose a robust elastic net (REN) model for high-dimensional sparse regression and give its performance guarantees (both the statistical error bound and the optimization bound).


Latent Dictionary Learning for Sparse Representation based Classification

no code implementations CVPR 2014 Meng Yang, Dengxin Dai, Lilin Shen, Luc van Gool

Each dictionary atom is jointly learned with a latent vector, which associates this atom to the representation of different classes.

Classification Dictionary Learning +4

Collaborative Representation based Classification for Face Recognition

no code implementations11 Apr 2012 Lei Zhang, Meng Yang, Xiangchu Feng, Yi Ma, David Zhang

It is widely believed that the l1- norm sparsity constraint on coding coefficients plays a key role in the success of SRC, while its use of all training samples to collaboratively represent the query sample is rather ignored.

Classification Face Recognition +3

Regularized Robust Coding for Face Recognition

no code implementations20 Feb 2012 Meng Yang, Lei Zhang, Jian Yang, David Zhang

Recently the sparse representation based classification (SRC) has been proposed for robust face recognition (FR).

Face Recognition Robust Face Recognition +1

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