10 papers
SenseFlow: A Physics-Informed and Self-Ensembling Iterative Framework for Power Flow Estimation
Zhen Zhao, Wenqi Huang, Zicheng Wang +3
Power flow estimation plays a vital role in ensuring the stability and reliability of electrical power systems, particularly in the context of growing network complexities and rene…
DiN: Diffusion Model for Robust Medical VQA with Semantic Noisy Labels
Erjian Guo, Zhen Zhao, Zicheng Wang +3
Medical Visual Question Answering (Med-VQA) systems benefit the interpretation of medical images containing critical clinical information. However, the challenge of noisy labels an…
Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels
Erjian Guo, Zicheng Wang, Zhen Zhao +1
Accurate medical image segmentation is often hindered by noisy labels in training data, due to the challenges of annotating medical images. Prior research works addressing noisy la…
SOEDiff: Efficient Distillation for Small Object Editing
Yiming Wu, Qihe Pan, Zhen Zhao +3
In this paper, we delve into a new task known as small object editing (SOE), which focuses on text-based image inpainting within a constrained, small-sized area. Despite the remark…
UniBrain: A Unified Model for Cross-Subject Brain Decoding
Zicheng Wang, Zhen Zhao, Luping Zhou +1
Brain decoding aims to reconstruct original stimuli from fMRI signals, providing insights into interpreting mental content. Current approaches rely heavily on subject-specific mode…
MoTe: Learning Motion-Text Diffusion Model for Multiple Generation Tasks
Yiming Wu, Wei Ji, Kecheng Zheng +2
Recently, human motion analysis has experienced great improvement due to inspiring generative models such as the denoising diffusion model and large language model. While the exist…