1 code implementation • 12 May 2024 • Hu Wang, Congbo Ma, Yuyuan Liu, Yuanhong Chen, Yu Tian, Jodie Avery, Louise Hull, Gustavo Carneiro
This cross-modal knowledge distillation produces a highly accurate model even with the absence of influential modalities.
no code implementations • 2 Oct 2023 • Hu Wang, Yuanhong Chen, Congbo Ma, Jodie Avery, Louise Hull, Gustavo Carneiro
Then, cross-modal knowledge distillation is performed between teacher and student modalities for each task to push the model parameters to a point that is beneficial for all tasks.
no code implementations • CVPR 2023 • Hu Wang, Yuanhong Chen, Congbo Ma, Jodie Avery, Louise Hull, Gustavo Carneiro
This is achieved from a strategy that relies on auxiliary tasks based on distribution alignment and domain classification, in addition to a residual feature fusion procedure.
no code implementations • 13 Sep 2022 • Congbo Ma, Wei Emma Zhang, Pitawelayalage Dasun Dileepa Pitawela, Yutong Qu, Haojie Zhuang, Hu Wang
One effective way is to encode document positional information to assist models in capturing cross-document relations.
no code implementations • 22 Jul 2022 • Hu Wang, Jianpeng Zhang, Yuanhong Chen, Congbo Ma, Jodie Avery, Louise Hull, Gustavo Carneiro
Multi-modal learning focuses on training models by equally combining multiple input data modalities during the prediction process.
no code implementations • 23 Sep 2021 • Congbo Ma, Wei Emma Zhang, Hu Wang, Shubham Gupta, Mingyu Guo
In this work, we develop a neural network based model which leverages dependency parsing to capture cross-positional dependencies and grammatical structures.
no code implementations • 20 Jul 2021 • Zihan Wang, Olivia Byrnes, Hu Wang, Ruoxi Sun, Congbo Ma, Huaming Chen, Qi Wu, Minhui Xue
The advancement of secure communication and identity verification fields has significantly increased through the use of deep learning techniques for data hiding.
no code implementations • 19 Apr 2021 • Hu Wang, Congbo Ma, Jianpeng Zhang, Gustavo Carneiro
Current deep image super-resolution (SR) approaches attempt to restore high-resolution images from down-sampled images or by assuming degradation from simple Gaussian kernels and additive noises.
no code implementations • 24 Jan 2021 • Hu Wang, Hao Chen, Qi Wu, Congbo Ma, Yidong Li, Chunhua Shen
To address these issues, in this work we carefully design our settings and propose a new dataset including both synthetic and real traffic data in more complex scenarios.
no code implementations • 10 Nov 2020 • Congbo Ma, Wei Emma Zhang, Mingyu Guo, Hu Wang, Quan Z. Sheng
Multi-document summarization (MDS) is an effective tool for information aggregation that generates an informative and concise summary from a cluster of topic-related documents.
no code implementations • 21 Jul 2020 • Congbo Ma, Hu Wang, Steven C. H. Hoi
Automated disease classification of radiology images has been emerging as a promising technique to support clinical diagnosis and treatment planning.
no code implementations • 21 Jul 2020 • Congbo Ma, Xiaowei Yang, Hu Wang
The experimental results on synthetic data and real-world data show the ROCP algorithm is able to cope with CP decomposition for large-scale tensors with arbitrary number of dimensions.
2 code implementations • 22 Dec 2019 • Hu Wang, Guansong Pang, Chunhua Shen, Congbo Ma
To enable unsupervised learning on those domains, in this work we propose to learn features without using any labelled data by training neural networks to predict data distances in a randomly projected space.