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cs.CV2026

UniField: A Unified Field-Aware MRI Enhancement Framework

Yiyang Lin, Chenhui Wang, Zhihao Peng +1

Magnetic Resonance Imaging (MRI) field-strength enhancement holds immense value for both clinical diagnostics and advanced research. However, existing methods typically focus on is…

cs.CV2026

Bridging Brain and Semantics: A Hierarchical Framework for Semantically Enhanced fMRI-to-Video Reconstruction

Yujie Wei, Chenglong Ma, Jianxiong Gao +6

Reconstructing dynamic visual experiences as videos from functional magnetic resonance imaging (fMRI) is pivotal for advancing the understanding of neural processes. However, curre…

cs.CV2026

Brain-WM: Brain Glioblastoma World Model

Chenhui Wang, Boyun Zheng, Liuxin Bao +4

Precise prognostic modeling of glioblastoma (GBM) under varying treatment interventions is essential for optimizing clinical outcomes. While generative AI has shown promise in simu…

cs.CV2026

Dynamic Differential Linear Attention: Enhancing Linear Diffusion Transformer for High-Quality Image Generation

Boyuan Cao, Xingbo Yao, Chenhui Wang +3

Diffusion transformers (DiTs) have emerged as a powerful architecture for high-fidelity image generation, yet the quadratic cost of self-attention poses a major scalability bottlen…

cs.CV2024

HiDiff: Hybrid Diffusion Framework for Medical Image Segmentation

Tao Chen, Chenhui Wang, Zhihao Chen +2

Medical image segmentation has been significantly advanced with the rapid development of deep learning (DL) techniques. Existing DL-based segmentation models are typically discrimi…

cs.CV2024

FLDM-VTON: Faithful Latent Diffusion Model for Virtual Try-on

Chenhui Wang, Tao Chen, Zhihao Chen +4

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, patt…