6 citations · 8 across the 18 of their papers we have counts for
8 papers · 1 filter
ProSMA-UNet: Decoder Conditioning for Proximal-Sparse Skip Feature Selection
Chun-Wun Cheng, Yanqi Cheng, Peiyuan Jing +4
Medical image segmentation commonly relies on U-shaped encoder-decoder architectures such as U-Net, where skip connections preserve fine spatial detail by injecting high-resolution…
3D Wavelet-Based Structural Priors for Controlled Diffusion in Whole-Body Low-Dose PET Denoising
Peiyuan Jing, Yue Yang, Chun-Wun Cheng +8
Low-dose Positron Emission Tomography (PET) imaging reduces patient radiation exposure but suffers from increased noise that degrades image quality and diagnostic reliability. Alth…
MAP-Diff: Multi-Anchor Guided Diffusion for Progressive 3D Whole-Body Low-Dose PET Denoising
Peiyuan Jing, Chun-Wun Cheng, Liutao Yang +7
Low-dose Positron Emission Tomography (PET) reduces radiation exposure but suffers from severe noise and quantitative degradation. Diffusion-based denoising models achieve strong f…
Training-Free Dual Hyperbolic Adapters for Better Cross-Modal Reasoning
Yi Zhang, Chun-Wun Cheng, Junyi He +5
Recent research in Vision-Language Models (VLMs) has significantly advanced our capabilities in cross-modal reasoning. However, existing methods suffer from performance degradation…
DNA-Prior: Unsupervised Denoise Anything via Dual-Domain Prior
Yanqi Cheng, Chun-Wun Cheng, Jim Denholm +5
Medical imaging pipelines critically rely on robust denoising to stabilise downstream tasks such as segmentation and reconstruction. However, many existing denoisers depend on larg…
Cross-Modal Few-Shot Learning with Second-Order Neural Ordinary Differential Equations
Yi Zhang, Chun-Wun Cheng, Junyi He +4
We introduce SONO, a novel method leveraging Second-Order Neural Ordinary Differential Equations (Second-Order NODEs) to enhance cross-modal few-shot learning. By employing a simpl…
Where Do We Stand with Implicit Neural Representations? A Technical and Performance Survey
Amer Essakine, Yanqi Cheng, Chun-Wun Cheng +5
Implicit Neural Representations (INRs) have emerged as a paradigm in knowledge representation, offering exceptional flexibility and performance across a diverse range of applicatio…
NODE-Adapter: Neural Ordinary Differential Equations for Better Vision-Language Reasoning
Yi Zhang, Chun-Wun Cheng, Ke Yu +3
In this paper, we consider the problem of prototype-based vision-language reasoning problem. We observe that existing methods encounter three major challenges: 1) escalating resour…