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.
1 code implementation • 17 May 2024 • Mushui Liu, Jun Dan, Ziqian Lu, Yunlong Yu, Yingming Li, Xi Li
In this paper, we propose CM-UNet, comprising a CNN-based encoder for extracting local image features and a Mamba-based decoder for aggregating and integrating global information, facilitating efficient semantic segmentation of remote sensing images.
1 code implementation • 14 Jan 2024 • Zhengqing Fang, Shuowen Zhou, Zhouhang Yuan, Yuxuan Si, Mengze Li, Jinxu Li, Yesheng Xu, Wenjia Xie, Kun Kuang, Yingming Li, Fei Wu, Yu-Feng Yao
This study investigates the performance, interpretability, and clinical utility of KGDM in the diagnosis of infectious keratitis (IK), which is the leading cause of corneal blindness.
no code implementations • 17 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.
no code implementations • 11 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.
no code implementations • IEEE International Conference on Image Processing (ICIP) 2021 • Shengxiong Ouyang, Xinglu Wang, Kejie Lyu, Yingming Li
Cross domain weakly supervised object detection (CDWSOD), where we can get access to instance-level annotations in the source domain while only image-level annotations are available in the target domain, adapts object detectors from label-rich to label-poor domains.
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.
no code implementations • Findings of the Association for Computational Linguistics 2020 • Tao Jin, Siyu Huang, Yingming Li, Zhongfei Zhang
Tensor-based fusion methods have been proven effective in multimodal fusion tasks.
no code implementations • 23 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.
no code implementations • IJCNLP 2019 • Tao Jin, Siyu Huang, Yingming Li, Zhongfei Zhang
This paper addresses the challenging task of video captioning which aims to generate descriptions for video data.
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.
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.
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.
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.
no code implementations • 7 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.
no code implementations • 7 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.
1 code implementation • 21 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.
no code implementations • 3 Nov 2016 • Bin Liu, Zenglin Xu, Yingming Li
Another assumption of these methods is that a predefined rank should be known.
no code implementations • 3 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.
no code implementations • 12 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.