Search Results for author: Gangming Zhao

Found 21 papers, 10 papers with code

Progressive Conservative Adaptation for Evolving Target Domains

no code implementations7 Feb 2024 Gangming Zhao, Chaoqi Chen, Wenhao He, Chengwei Pan, Chaowei Fang, Jinpeng Li, Xilin Chen, Yizhou Yu

Moreover, as adjusting to the most recent target domain can interfere with the features learned from previous target domains, we develop a conservative sparse attention mechanism.

Domain Adaptation Meta-Learning +1

Leveraging Frequency Domain Learning in 3D Vessel Segmentation

no code implementations11 Jan 2024 Xinyuan Wang, Chengwei Pan, Hongming Dai, Gangming Zhao, Jinpeng Li, Xiao Zhang, Yizhou Yu

In this study, we leverage Fourier domain learning as a substitute for multi-scale convolutional kernels in 3D hierarchical segmentation models, which can reduce computational expenses while preserving global receptive fields within the network.


TeacherLM: Teaching to Fish Rather Than Giving the Fish, Language Modeling Likewise

no code implementations29 Oct 2023 Nan He, Hanyu Lai, Chenyang Zhao, Zirui Cheng, Junting Pan, Ruoyu Qin, Ruofan Lu, Rui Lu, Yunchen Zhang, Gangming Zhao, Zhaohui Hou, Zhiyuan Huang, Shaoqing Lu, Ding Liang, Mingjie Zhan

Based on TeacherLM-7. 1B, we augmented 58 NLP datasets and taught various student models with different parameters from OPT and BLOOM series in a multi-task setting.

Data Augmentation Language Modelling

Identity-Preserving Talking Face Generation with Landmark and Appearance Priors

1 code implementation CVPR 2023 Weizhi Zhong, Chaowei Fang, Yinqi Cai, Pengxu Wei, Gangming Zhao, Liang Lin, Guanbin Li

Prior landmark characteristics of the speaker's face are employed to make the generated landmarks coincide with the facial outline of the speaker.

Talking Face Generation

Graph Convolution Based Cross-Network Multi-Scale Feature Fusion for Deep Vessel Segmentation

no code implementations6 Jan 2023 Gangming Zhao, Kongming Liang, Chengwei Pan, Fandong Zhang, Xianpeng Wu, Xinyang Hu, Yizhou Yu

To tackle the challenges caused by the sparsity and anisotropy of vessels, a higher percentage of graph nodes are distributed in areas that potentially contain vessels while a higher percentage of edges follow the orientation of potential nearbyvessels.


BEV@DC: Bird's-Eye View Assisted Training for Depth Completion

no code implementations CVPR 2023 Wending Zhou, Xu Yan, Yinghong Liao, Yuankai Lin, Jin Huang, Gangming Zhao, Shuguang Cui, Zhen Li

In practice, the proposed BEV@DC model comprehensively takes advantage of LiDARs with rich geometric details in training, employing an enhanced depth completion manner in inference, which takes only images (RGB and depth) as input.

Autonomous Driving Depth Completion

Mix and Reason: Reasoning over Semantic Topology with Data Mixing for Domain Generalization

no code implementations14 Oct 2022 Chaoqi Chen, Luyao Tang, Feng Liu, Gangming Zhao, Yue Huang, Yizhou Yu

Domain generalization (DG) enables generalizing a learning machine from multiple seen source domains to an unseen target one.

Domain Generalization Relational Reasoning

Deep 3D Vessel Segmentation based on Cross Transformer Network

1 code implementation22 Aug 2022 Chengwei Pan, Baolian Qi, Gangming Zhao, Jiaheng Liu, Chaowei Fang, Dingwen Zhang, Jinpeng Li

In CTN, a transformer module is constructed in parallel to a U-Net to learn long-distance dependencies between different anatomical regions; and these dependencies are communicated to the U-Net at multiple stages to endow it with global awareness.

Computed Tomography (CT) Segmentation

Diagnose Like a Radiologist: Hybrid Neuro-Probabilistic Reasoning for Attribute-Based Medical Image Diagnosis

no code implementations19 Aug 2022 Gangming Zhao, Quanlong Feng, Chaoqi Chen, Zhen Zhou, Yizhou Yu

On the LIDC-IDRI benchmark dataset for benign-malignant classification of pulmonary nodules in CT images, our method achieves a new state-of-the-art accuracy of 95. 36\% and an AUC of 96. 54\%.


Computer-aided Tuberculosis Diagnosis with Attribute Reasoning Assistance

1 code implementation1 Jul 2022 Chengwei Pan, Gangming Zhao, Junjie Fang, Baolian Qi, Jiaheng Liu, Chaowei Fang, Dingwen Zhang, Jinpeng Li, Yizhou Yu

Although deep learning algorithms have been intensively developed for computer-aided tuberculosis diagnosis (CTD), they mainly depend on carefully annotated datasets, leading to much time and resource consumption.

Attribute Relational Reasoning +1

Learning Locality and Isotropy in Dialogue Modeling

1 code implementation29 May 2022 Han Wu, Haochen Tan, Mingjie Zhan, Gangming Zhao, Shaoqing Lu, Ding Liang, Linqi Song

Existing dialogue modeling methods have achieved promising performance on various dialogue tasks with the aid of Transformer and the large-scale pre-trained language models.

BOAT: Bilateral Local Attention Vision Transformer

1 code implementation31 Jan 2022 Tan Yu, Gangming Zhao, Ping Li, Yizhou Yu

To improve efficiency, recent Vision Transformers adopt local self-attention mechanisms, where self-attention is computed within local windows.

MVCNet: Multiview Contrastive Network for Unsupervised Representation Learning for 3D CT Lesions

no code implementations17 Aug 2021 Penghua Zhai, Huaiwei Cong, Gangming Zhao, Chaowei Fang, Jinpeng Li, Ting Cai, Huiguang He

To avoid the subjectivity associated with these methods, we propose the MVCNet, a novel unsupervised three dimensional (3D) representation learning method working in a transformation-free manner.

Computed Tomography (CT) Representation Learning +1

GraphFPN: Graph Feature Pyramid Network for Object Detection

2 code implementations ICCV 2021 Gangming Zhao, Weifeng Ge, Yizhou Yu

State-of-the-art methods for multi-scale feature learning focus on performing feature interactions across space and scales using neural networks with a fixed topology.

Object object-detection +1

Multi-scale Matching Networks for Semantic Correspondence

1 code implementation ICCV 2021 Dongyang Zhao, Ziyang Song, Zhenghao Ji, Gangming Zhao, Weifeng Ge, Yizhou Yu

We follow the coarse-to-fine matching strategy and build a top-down feature and matching enhancement scheme that is coupled with the multi-scale hierarchy of deep convolutional neural networks.

Computational Efficiency Semantic correspondence

GREN: Graph-Regularized Embedding Network for Weakly-Supervised Disease Localization in X-ray Images

1 code implementation14 Jul 2021 Baolian Qi, Gangming Zhao, Xin Wei, Changde Du, Chengwei Pan, Yizhou Yu, Jinpeng Li

To model the relationship, we propose the Graph Regularized Embedding Network (GREN), which leverages the intra-image and inter-image information to locate diseases on chest X-ray images.

Decision Making

Contralaterally Enhanced Networks for Thoracic Disease Detection

no code implementations9 Oct 2020 Gangming Zhao, Chaowei Fang, Guanbin Li, Licheng Jiao, Yizhou Yu

Aimed at improving the performance of existing detection methods, we propose a deep end-to-end module to exploit the contralateral context information for enhancing feature representations of disease proposals.

Rethink ReLU to Training Better CNNs

no code implementations19 Sep 2017 Gangming Zhao, Zhao-Xiang Zhang, He Guan, Peng Tang, Jingdong Wang

Most of convolutional neural networks share the same characteristic: each convolutional layer is followed by a nonlinear activation layer where Rectified Linear Unit (ReLU) is the most widely used.

Cannot find the paper you are looking for? You can Submit a new open access paper.