no code implementations • 22 Apr 2024 • Chenhui Wang, Tao Chen, Zhihao Chen, Zhizhong Huang, Taoran Jiang, Qi Wang, Hongming Shan
Despite their impressive generative performance, latent diffusion model-based virtual try-on (VTON) methods lack faithfulness to crucial details of the clothes, such as style, pattern, and text.
1 code implementation • 10 Mar 2024 • Zhihao Chen, Tao Chen, Chenhui Wang, Chuang Niu, Ge Wang, Hongming Shan
While various deep learning methods were proposed for low-dose computed tomography (CT) denoising, they often suffer from over-smoothing, blurring, and lack of explainability.
1 code implementation • 19 Jan 2024 • Chenhui Wang, Yiming Lei, Tao Chen, Junping Zhang, Yuxin Li, Hongming Shan
Inspired by that various longitudinal biomarkers and cognitive measurements present an ordinal pathway on AD progression, we propose a novel Hybrid-granularity Ordinal PrototypE learning (HOPE) method to characterize AD ordinal progression for MCI progression prediction.
no code implementations • 10 Apr 2023 • Tao Chen, Chenhui Wang, Hongming Shan
Second, by leveraging the stochastic nature of the diffusion model, our BerDiff randomly samples the initial Bernoulli noise and intermediate latent variables multiple times to produce a range of diverse segmentation masks, which can highlight salient regions of interest that can serve as valuable references for radiologists.
no code implementations • 5 Aug 2022 • Tong Xu, Lin Wang, Wu Ning, Chunyan Lyu, Kejun Wang, Chenhui Wang
As a study on the efficient usage of data, Multi-source Unsupervised Domain Adaptation transfers knowledge from multiple source domains with labeled data to an unlabeled target domain.
Multi-Source Unsupervised Domain Adaptation Unsupervised Domain Adaptation
no code implementations • 23 Apr 2021 • Xinnan Ding, Kejun Wang, Chenhui Wang, Tianyi Lan, Liangliang Liu
As a unique and promising biometric, video-based gait recognition has broad applications.
no code implementations • 24 Nov 2020 • Jing Chen, Chenhui Wang, Kejun Wang, Meichen Liu
A large number of experimental results show that the proposed CEDNN is obviously better than the traditional deep learning method on DISFA+ and CK+ datasets.
no code implementations • 24 Jul 2020 • Jing Chen, Chenhui Wang, Kejun Wang, Chaoqun Yin, Cong Zhao, Tao Xu, Xinyi Zhang, Ziqiang Huang, Meichen Liu, Tao Yang
Existing multimodal emotion databases in the real-world conditions are few and small, with a limited number of subjects and expressed in a single language.