[HTML][HTML] A survey on GANs for computer vision: Recent research, analysis and taxonomy

G Iglesias, E Talavera, A Díaz-Álvarez - Computer Science Review, 2023 - Elsevier
In the last few years, there have been several revolutions in the field of deep learning,
mainly headlined by the large impact of Generative Adversarial Networks (GANs). GANs not …

Closed-loop matters: Dual regression networks for single image super-resolution

Y Guo, J Chen, J Wang, Q Chen… - Proceedings of the …, 2020 - openaccess.thecvf.com
Deep neural networks have exhibited promising performance in image super-resolution
(SR) by learning a nonlinear map** function from low-resolution (LR) images to high …

Scalable optimal transport methods in machine learning: A contemporary survey

A Khamis, R Tsuchida, M Tarek… - IEEE transactions on …, 2024 - ieeexplore.ieee.org
Optimal Transport (OT) is a mathematical framework that first emerged in the eighteenth
century and has led to a plethora of methods for answering many theoretical and applied …

Dense regression network for video grounding

R Zeng, H Xu, W Huang, P Chen… - Proceedings of the …, 2020 - openaccess.thecvf.com
We address the problem of video grounding from natural language queries. The key
challenge in this task is that one training video might only contain a few annotated …

Location-aware graph convolutional networks for video question answering

D Huang, P Chen, R Zeng, Q Du, M Tan… - Proceedings of the AAAI …, 2020 - ojs.aaai.org
We addressed the challenging task of video question answering, which requires machines
to answer questions about videos in a natural language form. Previous state-of-the-art …

Collaborative unsupervised domain adaptation for medical image diagnosis

Y Zhang, Y Wei, Q Wu, P Zhao, S Niu… - … on Image Processing, 2020 - ieeexplore.ieee.org
Deep learning based medical image diagnosis has shown great potential in clinical
medicine. However, it often suffers two major difficulties in real-world applications: 1) only …

Generative low-bitwidth data free quantization

S Xu, H Li, B Zhuang, J Liu, J Cao, C Liang… - Computer Vision–ECCV …, 2020 - Springer
Neural network quantization is an effective way to compress deep models and improve their
execution latency and energy efficiency, so that they can be deployed on mobile or …

Inter-class and inter-domain semantic augmentation for domain generalization

M Wang, Y Liu, J Yuan, S Wang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The domain generalization approach seeks to develop a universal model that performs well
on unknown target domains with the aid of diverse source domains. Data augmentation has …

One-dm: One-shot diffusion mimicker for handwritten text generation

G Dai, Y Zhang, Q Ke, Q Guo, S Huang - European Conference on …, 2024 - Springer
Existing handwritten text generation methods often require more than ten handwriting
samples as style references. However, in practical applications, users tend to prefer a …